KR20210043695A - Method of determining candidate patterns from a set of patterns in a patterning process - Google Patents

Abstract

In this specification, a method of determining candidate patterns from a set of patterns of a patterning process is described. The method comprises a first comprising (i) a set of patterns in the patterning process, (ii) a search pattern having a first feature and a second feature, and (iii) a relative position between the first feature and the second feature of the search pattern. Obtaining a search condition; And determining a first set of candidate patterns from the set of patterns that satisfy a first search condition associated with the first feature and the second feature of the search pattern.

Description

Method of determining candidate patterns from a set of patterns in a patterning process

This application claims the priority of US application 62/735,377, filed September 24, 2018, which is incorporated herein by reference in its entirety.

The description herein relates generally to a patterning process and to the search for a desired pattern, and more particularly to an apparatus or method for determining patterns in a substrate pattern or field pattern that match the desired pattern.

A lithographic apparatus is a machine that applies a desired pattern onto a target portion of a substrate. Lithographic apparatus can be used, for example, in the manufacture of integrated circuits (ICs). In that situation, a patterning device, alternatively referred to as a mask or reticle, can be used to create a circuit pattern corresponding to the individual layers of the IC, which pattern is a substrate (e.g., silicon) with a layer of radiation-sensitive material (resist). Wafer) onto a target portion (eg, comprising a portion of a die, one or several dies). In general, a single substrate will contain a network of adjacent target portions that are successively exposed. Known lithographic apparatuses scan a pattern in a given direction ("scanning"-direction) through a beam, a so-called stepper in which each target portion is irradiated by exposing the entire pattern onto the target portion at once, while It includes a so-called scanner in which each target portion is irradiated by synchronously scanning the substrate in parallel or anti-parallel with the direction.

Prior to transferring the circuit pattern from the patterning device to the substrate, the substrate may be subjected to various procedures such as priming, resist coating and soft bake. After exposure, the substrate may undergo other procedures such as post-exposure bake (PEB), development, hard bake, and measurement/inspection of the transferred circuit pattern. These series of procedures are used as the basis for constructing individual layers of a device, such as an IC. The substrate can then be subjected to various processes such as etching, ion-implantation (doping), metallization, oxidation, chemical-mechanical polishing, etc., all intended to finish individual layers of the device. If multiple layers are required in the device, the entire process or variations thereof are repeated for each layer. Eventually, a device will be present in each target portion on the substrate. Thereafter, these devices are separated from each other by techniques such as dicing or sawing, and the individual devices can be mounted on a carrier or the like connected to the pins.

Thus, manufacturing devices such as semiconductor devices typically involves processing a substrate (e.g., a semiconductor wafer) using multiple fabrication processes to form the various features and multiple layers of the devices. . These layers and features are typically fabricated and processed using, for example, deposition, lithography, etching, chemical-mechanical polishing, and ion implantation. Multiple devices may be fabricated on a plurality of dies on a substrate and then separated into individual devices. This device manufacturing process can be considered a patterning process. The patterning process involves a patterning step, such as optical and/or nanoimprint lithography, in which a pattern on the patterning device is transferred to a substrate using a patterning device in a lithographic apparatus. It involves one or more related pattern processing steps, such as baking of the substrate using a tool, etching of the pattern using an etching apparatus, and the like.

According to an embodiment, a method of determining candidate patterns from a set of patterns of a patterning process is provided. The method includes (i) a set of patterns in the patterning process, (ii) a search pattern having a first feature and a second feature, and (iii) a relative position between the first feature and the second feature of the search pattern. Obtaining a first search condition to include; And determining, via the processor, a first set of candidate patterns from a set of patterns that satisfy a first search condition associated with the first feature and the second feature of the search pattern. In one embodiment, the second feature is adjacent to the first feature.

In one embodiment, the relative position is defined between the element of the first feature and the element of the second feature of the search pattern.

In one embodiment, the element includes an edge and/or vertex of each feature.

In one embodiment, the first search condition further comprises a tolerance limit associated with the dimensions of the features and/or the relative position between the elements of the features.

In one embodiment, the first feature and the second feature are on the same layer.

In one embodiment, the first feature and the second feature are on different layers.

In one embodiment, the method includes: obtaining a bounding box around the search pattern and a second search condition associated with the feature and bounding box of the search pattern; And determining, via the processor, a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the bounding box.

In one embodiment, the second search condition includes a relative position between an edge of the bounding box and an edge of a feature of the search pattern.

In one embodiment, the relative position is the distance and/or angle between the edge of the bounding box and the edge of the feature of the search pattern.

In one embodiment, the second search condition further comprises a tolerance limit associated with the relative position between the bounding box and the element of the feature of the search pattern.

In one embodiment, the second search condition is associated with the feature of the search pattern closest to the bounding box.

In one embodiment, determining the second set of candidate patterns further comprises comparing one or more parameters of the features of the search pattern with a corresponding one or more parameters of the features of the set of patterns.

In one embodiment, the one or more parameters include: edge of the feature; The size of the feature; And at least one of the topologies of the feature.

In one embodiment, determining the second set of candidate patterns includes adjusting a bounding box around the search pattern based on a second search condition; And determining a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the adjusted bounding box.

In one embodiment, adjusting the bounding box includes increasing and/or decreasing the size of the bounding box for increasing and/or decreasing the size of the features of the second search condition and the field pattern.

In one embodiment, the amount of increase and/or decrease in the size of the bounding box is within a tolerance limit associated with the relative position between the bounding box and the elements of the feature in the search pattern.

In one embodiment, the set of patterns is obtained from an image of patterns of a printed substrate and/or simulated patterns of a substrate.

In one embodiment, the set of patterns is obtained from a scanning electron microscope image.

In one embodiment, the search pattern includes a plurality of features, the plurality of features being in the same layer of the substrate and/or different layers of the substrate.

Further, according to an embodiment, a method of determining candidate patterns from a set of patterns is provided. The method comprises (i) a first set of candidate patterns from a set of patterns based on a first search condition associated with features of the search pattern, (ii) a bounding box around the search pattern, and (iii) a feature of the search pattern. And obtaining a second search condition associated with the bounding box. And determining a second set of candidate patterns from the first set of candidate patterns based on the second search condition.

In one embodiment, the second search condition is the distance and/or angle between the edge of the bounding box and the edge of the feature of the search pattern.

In one embodiment, the second search condition further comprises a tolerance limit associated with a distance and/or angle between the bounding box and an element of the feature of the search pattern.

In one embodiment, determining the second set of candidate patterns includes comparing one or more parameters of a feature of the search pattern with a corresponding one or more parameters of a feature of the set of patterns; And based on the comparison, selecting a subset of patterns from the first set of candidate patterns excluding patterns with topology mismatch.

In one embodiment, the one or more parameters include: edge of the feature; The size of the feature; And at least one of the topologies of the feature.

In one embodiment, determining the second set of candidate patterns includes adjusting a bounding box around the search pattern based on a second search condition; And determining a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the adjusted bounding box.

In one embodiment, adjusting the bounding box includes increasing and/or decreasing the size of the bounding box as a function of the size of the feature in the second search condition and the field pattern.

In one embodiment, the amount of increase and/or decrease in the size of the bounding box is within a tolerance limit associated with the relative position between the bounding box and the elements of the feature in the search pattern.

Further, according to an embodiment, a method of determining candidate patterns from a set of patterns of a patterning process is provided. The method comprises (i) a first set of candidate patterns from a set of patterns based on a first search condition associated with features of the search pattern, (ii) a bounding box around the search pattern, and (iii) a feature of the search pattern. And obtaining a second search condition associated with the bounding box. And determining a second set of candidate patterns from the first set of candidate patterns based on the second search condition, wherein the second set of candidate patterns has an extra feature that is not included in the search pattern. Include candidate patterns.

In one embodiment, the additional features are adjacent to and within the bounding box of the features of the search pattern.

In one embodiment, the additional features are on the same layer and/or on a different layer as the features of the search pattern.

In one embodiment, the additional feature is not associated with a bounding box or constraint on the features of the search pattern.

In one embodiment, determining the second set of candidate patterns includes comparing one or more parameters of a feature of the search pattern with a corresponding one or more parameters of a feature of the set of patterns; And based on the comparison, selecting patterns from the first set of candidate patterns without excluding patterns having topology mismatching.

In one embodiment, the one or more parameters include: edge of the feature; The size of the feature; And at least one of the topologies of the feature.

Further, according to an embodiment, a method of determining candidate patterns from a set of patterns of a patterning process is provided. The method includes applying a first condition between a first feature and a second feature of a search pattern through an interface; Determining, through the processor, a first set of candidate patterns from the set of patterns based on a first condition; Drawing, via the interface, a bounding box around the search pattern; Applying, via the interface, a second condition between the bounding box and the first feature or the second feature; And determining, through the processor, a second set of candidate patterns from the first set of candidate patterns based on a second condition, wherein the second set of candidate patterns is a candidate having additional features not included in the search pattern. Includes the pattern.

In one embodiment, applying the first condition includes selecting an edge of a first feature and an edge of a second feature of the search pattern; Allocating a distance between the selected edges; And/or assigning a tolerance limit to the distance between the selected edges.

In addition, according to an embodiment, a method of generating a search pattern database is provided. The method comprises obtaining a set of patterns, the pattern of the set of patterns comprising a plurality of features; Applying, via an interface, a set of search conditions to the set of patterns to generate a set of search patterns-the search pattern is associated with the search condition; Evaluating, via the processor, whether there is a conflict between the one or more search conditions associated with the one or more features of the set of patterns; And storing, via the processor, a set of search patterns and associated search conditions for which there is no conflict.

In one embodiment, evaluating a collision includes identifying features of a set of patterns having the same search condition; And/or determining whether the search conditions exceed a preset threshold associated with a feature of the pattern in the set of patterns. And/or displaying the identified features to modify the conditions to eliminate the conflict.

In addition, according to an embodiment of the present invention, there is provided a computer program product including a non-transitory computer-readable medium in which instructions are recorded, and the instructions are any of the above-described methods when executed by a computer. Implement the steps of the methods.

1 schematically shows a lithographic apparatus according to an embodiment.
2 schematically shows an embodiment of a lithographic cell or cluster according to an embodiment.
3A to 3C are exemplary pattern definitions associated with a search pattern according to an embodiment.
4 is a flowchart of a method of determining candidate patterns from a set of patterns in a patterning process according to an exemplary embodiment.
5 is a flowchart of another method of determining candidate patterns from a set of patterns in a patterning process according to an embodiment.
6 is a flowchart of another method of determining candidate patterns from a set of patterns in a patterning process according to an embodiment.
7 is a flowchart of another method of determining candidate patterns from a set of patterns in a patterning process according to an embodiment.
8 is a flowchart of a method of generating a search pattern according to an exemplary embodiment.
9 is an example of a search pattern having a plurality of features according to an embodiment.
10 is an example of a field pattern or a printed substrate pattern according to an embodiment.
11A and 11B are snapshots of results of intermediate steps involved in determining a set of candidate patterns from the field pattern of FIG. 10 matching the search pattern of FIG. 9 according to an embodiment.
12 shows an exemplary adjustment of the bounding boxes of FIGS. 11A and 11B according to an embodiment.
13 is an example of search results in which second candidate patterns include additional features according to an embodiment.
14 schematically shows an embodiment of a scanning electron microscope (SEM) according to an embodiment.
15 schematically shows an embodiment of an electron beam inspection apparatus according to an embodiment.
16 is a block diagram of an exemplary computer system according to one embodiment.
17 is a schematic diagram of another lithographic projection apparatus according to an embodiment.
Fig. 18 is a more detailed view of the device of Fig. 17 according to one embodiment.
19 is a more detailed diagram of a source collector module of the apparatus of FIGS. 17 and 18 according to an embodiment.
The embodiments will now be described in detail with reference to the drawings provided as illustrative examples to enable a person skilled in the art to practice the embodiments. In particular, the numbers and examples below are not intended to limit the scope to a single embodiment, and other embodiments are possible by exchanging some or all of the elements described or shown. Where convenient, the same reference numbers will be used throughout the drawings to refer to the same or similar parts. When certain elements of these embodiments can be partially or completely implemented using known elements, only portions necessary for understanding the embodiments of these known elements will be described, and details of other portions of these known elements will be described. Descriptions will be omitted so as not to obscure the description of the embodiments. In this specification, an embodiment representing a single component should not be regarded as limiting; Rather, unless explicitly stated otherwise in the specification, a range is intended to include other embodiments including a plurality of the same elements, and vice versa. Moreover, Applicants are not intended to take any term in the specification or claims to be taken in an unusual or special meaning unless expressly stated as such. In addition, the scope includes current and future known equivalents to the elements mentioned herein by way of example.

Prior to describing the embodiments in detail, it is beneficial to present an exemplary environment in which the embodiments may be implemented.

1 schematically shows an embodiment of a lithographic apparatus LA. The device is:

-An illumination system (illuminator) IL configured to condition the radiation beam B (eg UV radiation or DUV radiation);

-A support structure (e.g., a support structure (e.g., a mask) configured to support the patterning device (e.g., a mask) MA and connected to a first positioner PM configured to accurately position the patterning device according to predetermined parameters Mask table) (MT);

-A substrate table (e.g., a resist-coated wafer) W configured to hold and connected to a second positioner PW configured to accurately position the substrate according to predetermined parameters. For example, a wafer table) (WT) (eg, WTa, WTb, or both); And

-Configured to project the pattern imparted to the radiation beam B by the patterning device MA onto the target portion C (including, for example, one or more dies, commonly referred to as a field) of the substrate W A projection system (eg, a refractive projection lens system) PS, which is supported on a reference frame (RF).

As shown herein, the device is configured in a transmissive type (eg, employing a transmissive mask). Alternatively, the device may be configured in a reflective type (eg employing a programmable mirror array of the type as mentioned above, or employing a reflective mask).

The illuminator IL receives a radiation beam from the radiation source SO. For example, when the source is an excimer laser, the source and the lithographic apparatus may be separate entities. In this case, the source is not considered to form part of the lithographic apparatus, and the radiation beam is, for example, with the aid of a beam delivery system (BD) comprising a suitable directing mirror and/or a beam expander, the source ( SO) passes to the illuminator IL. In other cases, for example, if the source is a mercury lamp, the source may be an integral part of the device. The source SO and the illuminator IL, together with the beam delivery system BD, may be referred to as a radiation system, if necessary.

The illuminator IL may change the intensity distribution of the beam. The illuminator may be arranged to limit the radius size of the radiation beam such that the intensity distribution is non-zero within the annular region of the pupil plane of the illuminator IL. Additionally or alternatively, the illuminator IL may be operable to limit the distribution of the beam in the pupil plane such that the intensity distribution is non-zero in a plurality of equally spaced sectors in the pupil plane. The intensity distribution of the radiation beam in the pupil plane of the illuminator IL may be referred to as an illumination mode.

Accordingly, the illuminator IL may include an adjuster AM configured to adjust the (angular/space) intensity distribution of the beam. In general, at least the outer and/or inner radial extent (commonly referred to as σ-outer and σ-inner, respectively) of the intensity distribution in the pupil plane of the illuminator can be adjusted. The illuminator IL may be operable to change the angular distribution of the beam. For example, the illuminator may be operable to change the angular magnitude, and the number of sectors in the pupil plane where the intensity distribution is not zero. By adjusting the intensity distribution of the beam in the pupil plane of the illuminator, different illumination modes can be achieved. For example, by limiting the radius and angular magnitude of the intensity distribution in the pupil plane of the illuminator (IL), the intensity distribution can be multi-pole, e.g. dipole, quadrupole or hexapole distribution. It can have a (multi-pole) distribution. A desired illumination mode can be obtained, for example, by inserting optics providing its illumination mode into the illuminator IL, or by using a spatial light modulator.

The illuminator IL may be operable to change the polarization of the beam, and may be operable to adjust the polarization using the adjuster AM. The polarization state of the radiation beam over the pupil plane of the illuminator IL may be referred to as a polarization mode. The use of different polarization modes can allow a greater contrast to be achieved in the image formed on the substrate W. The radiation beam may not be polarized. Alternatively, the illuminator can be arranged to linearly polarize the radiation beam. The polarization direction of the radiation beam may change over the pupil plane of the illuminator IL. The direction of polarization of the radiation may be different in different regions within the pupil plane of the illuminator IL. The polarization state of the radiation can be selected depending on the illumination mode. For multipole illumination modes, the polarization of each pole of the radiation beam may be generally perpendicular to the position vector of that pole within the pupil plane of the illuminator IL. For example, for a dipole illumination mode, the radiation may be linearly polarized in a direction substantially perpendicular to the line bisecting the two opposing sectors of the dipole. The radiation beam can be polarized in one of two different orthogonal directions, which can be referred to as X-polarized and Y-polarized states. For a quadrupole illumination mode, radiation in a sector of each pole may be linearly polarized in a direction substantially perpendicular to the line bisecting that sector. This polarization mode can be referred to as XY polarization. Similarly, for a hexapole illumination mode, radiation in a sector of each pole can be linearly polarized in a direction substantially perpendicular to the line bisecting that sector. This polarization mode can be referred to as TE polarization.

In addition, the illuminator IL generally includes various other components, such as an integrator IN and a condenser CO. The lighting system may include various types of optical components, such as refractive, reflective, magnetic, electromagnetic, electrostatic or other types of optical components, or any combination thereof, to direct, shape, or control radiation. have.

Thus, the illuminator provides a conditioned radiation beam B having a desired uniformity and intensity distribution in the cross section of the radiation beam B.

The support structure MT supports the patterning device in a manner that depends on the orientation of the patterning device, the design of the lithographic apparatus, and other conditions such as, for example, whether the patterning device is held in a vacuum environment. The support structure may use mechanical, vacuum, electrostatic, or other clamping techniques to hold the patterning device. The support structure can be, for example, a frame or a table that can be fixed or movable as needed. The support structure can ensure that the patterning device is in a desired position with respect to the projection system, for example. Any use of the terms "reticle" or "mask" herein may be considered synonymous with the more general term "patterning device".

The term "patterning device" as used herein should be broadly interpreted as referring to any device that can be used to impart a pattern to a target portion of a substrate. In one embodiment, the patterning device is any device that can be used to impart a pattern in a cross-section of a radiation beam to create a pattern in a target portion of the substrate. The pattern imparted to the radiation beam does not exactly match the desired pattern in the target portion of the substrate, for example if the pattern comprises phase-shifting features or so-called assist features. It should be noted that it may not. In general, the pattern imparted to the radiation beam will correspond to a particular functional layer in a device being created in the target portion, such as an integrated circuit.

The patterning device may be transmissive or reflective. Examples of patterning devices include masks, programmable mirror arrays, and programmable LCD panels. Masks are well known in the field of lithography and include mask types such as binary, alternating phase-shift and attenuated phase-shift, and various hybrid mask types. One example of a programmable mirror array employs a matrix configuration of small mirrors, each of which can be individually tilted to reflect an incident radiation beam in different directions. The tilted mirrors impart a pattern to the beam of radiation reflected by the mirror matrix.

The term "projection system" as used herein, if appropriate for the exposure radiation used, or for other factors such as the use of immersion liquid or the use of vacuum, refraction, reflection, catadioptric, It should be broadly interpreted as encompassing any type of projection system including magnetic, electromagnetic and electrostatic optical systems, or any combination thereof. Any use of the term "projection lens" herein may be considered synonymous with the more general term "projection system".

The projection system PS has an optical transfer function that can be non-uniform, which can affect the pattern imaged on the substrate W. For unpolarized radiation, these effects can be explained fairly well by the two scalar maps, which are the transmission of radiation exiting the projection system PS as a function of its position within its pupil plane (apodi Apodization] and relative phase (aberration) will be described. These scalar maps, which can be referred to as transmission maps and relative phase maps, can be represented as a linear combination of a complete set of basis functions. A particularly convenient set is the Zernike polynomials, which form a set of orthogonal polynomials defined on a unit circle. Determination of each scalar map may involve determining the coefficients in this expansion. Because the Zernike polynomials are orthogonal on the unit circle, the Zernike coefficients are in turn calculated by calculating the inner product of each Zernike polynomial and the measured scalar map and dividing it by the square of the norm of that Zernike polynomial. Can be determined.

The transmission map and relative phase map are field and system dependent. That is, in general each projection system PS will have a different Zernike evolution for each field point (ie, each spatial location within its image plane). The relative phase of the projection system PS in the pupil plane is, for example, a point-like source in the object plane (i.e., the plane of the patterning device MA) of the projection system PS. source) through the projection system PS and measuring the wavefront (ie, traces of points having the same phase) using a shearing interferometer. The shearing interferometer is a common path interferometer and thus advantageously does not require a secondary reference beam to measure the wavefront. The shearing interferometer is a diffraction grating in the image plane of the projection system (i.e., substrate table WT), e.g., a two-dimensional grid, and a detector arranged to detect interference patterns in a plane conjugate to the pupil plane of the projection system PS. It may include. The interference pattern is related to the derivative of the phase of the radiation with respect to the coordinates of the pupil plane in the shearing direction. The detector may comprise an array of sensing elements such as, for example, a charge coupled device (CCD).

The projection system (PS) of the lithographic apparatus may not produce visible fringes, so the accuracy of the crystallization of the wavefront uses phase stepping techniques, e.g. by moving the diffraction grating. Can be improved. Stepping can be performed in a direction perpendicular to the scanning direction of the measurement and in the plane of the diffraction grating. The stepping range can be a grating period of 1, and at least 3 (uniformly distributed) phase steps can be used. Thus, for example, three scanning measurements can be performed in the y-direction, and each scanning measurement is performed for a different position in the x-direction. This stepping of the diffraction grating effectively converts the phase fluctuations into intensity fluctuations, allowing the phase information to be determined. The grating can be stepped in a direction perpendicular to the diffraction grating (z direction) to calibrate the detector.

The diffraction grating may be scanned successively in two vertical directions which may coincide with the axes x and y of the coordinate system of the projection system PS or have an angle equal to 45 degrees with respect to these axes. Scanning can be performed over an integer number of grating periods, for example 1 grating period. Scanning averages the phase fluctuations in one direction, causing the phase fluctuations in the other direction to be reconstructed. This causes the wavefront to be determined as a function of the two directions.

The transmission (apodization) of the projection system PS in the pupil plane is, for example, from a point-like source in the object plane of the projection system PS (i.e., the plane of the patterning device MA). PS), and using a detector to measure the intensity of the radiation in the conjugate plane to the pupil plane of the projection system PS. The same detector used to measure the wavefront can be used to determine the aberrations.

The projection system PS may include a plurality of optical (e.g., lens) elements, and adjust one or more of the optical elements to correct for aberrations (phase fluctuations across the pupil plane throughout the field). It may further include an adjustment mechanism (AM) configured to be. To achieve this, the adjustment mechanism may be operable to manipulate one or more optical (eg, lens) elements in the projection system PS in one or more different ways. The projection system may have a coordinate system whose optical axis extends in the z direction. The adjustment mechanisms include: ie displacing one or more optical elements; Tilting one or more optical elements; And/or modifying one or more optical elements. The displacement of the optical element can be in any direction (x, y, z or a combination thereof). The tilting of the optical element is usually out of the plane perpendicular to the optical axis by rotating around the axis of the x and/or y directions, but rotation around the z axis can be used for non-rotationally symmetric aspherical optical elements. have. The deformation of the optical element may include a low frequency shape (e.g., astigmatic) and/or a high frequency shape (e.g. free form aspheres). have. Deformation of the optical element can be effected, for example, by using one or more actuators to exert a force on one or more sides of the optical element, and/or by using one or more heating elements to heat one or more selected regions of the optical element. have. In general, it may not be possible to adjust the projection system PS to correct for apodization (transmission variation across the pupil plane). The transmission map of the projection system PS can be used when designing a patterning device (eg, a mask) MA for the lithographic apparatus LA. Using a computational lithography technique, the patterning device MA can be designed to at least partially correct for apodization.

The lithographic apparatus includes two (dual stage) or more tables (e.g., two or more substrate tables (WTa, WTb), two or more patterning device tables, a substrate table (WTa) and for example measuring and/or cleaning, etc. It can be configured in the form of having a table (WTb) under the projection system without a substrate designated to facilitate it. In such "multiple stage" machines, additional tables may be used in parallel, or preparatory steps may be performed on one or more other tables while one or more other tables are being used for exposure. For example, alignment measurements using the alignment sensor AS and/or level (height, slope, etc.) measurements using the level sensor LS may be performed.

Further, the lithographic apparatus may also be configured in a form in which at least a portion of the substrate can be covered with a liquid having a relatively high refractive index, such as water, in order to fill the space between the projection system and the substrate. The immersion liquid can also be applied to other spaces within the lithographic apparatus, for example between the patterning device and the projection system. Immersion techniques are well known in the art for increasing the numerical aperture of a projection system. The term "immersion" as used herein does not mean that a structure such as a substrate must be immersed in a liquid, but merely means that the liquid lies between the projection system and the substrate upon exposure.

Thus, in operation of the lithographic apparatus, the radiation beam is conditioned and provided by the illumination system IL. The radiation beam B is incident on a patterning device (eg, a mask) MA, which is held on a support structure (eg, a mask table) MT, and is patterned by the patterning device. When traversing the patterning device MA, the radiation beam B passes through the projection system PS, which focuses the beam on the target portion C of the substrate W. With the help of a second positioner PW and a position sensor IF (for example an interferometric device, a linear encoder, a 2-D encoder or a capacitive sensor), the substrate table WT is for example a radiation beam ( It can be accurately moved to position the different target portions C in the path of B). Similarly, the first positioner PM and another position sensor (not clearly shown in Fig. 1) can be used for radiation, for example after mechanical recovery from the mask library or during scanning. It can be used to accurately position the patterning device MA with respect to the path of the beam B. In general, movement of the support structure MT can be realized with the help of a long-stroke module (roughly positioning) and a short-stroke module (fine positioning), which 1 It forms a part of the position setter (PM). Similarly, the movement of the substrate table WT can be realized using a long-stroke module and a short-stroke module, which forms part of the second positioner PW. In the case of a stepper (as opposed to a scanner), the support structure MT may be connected or fixed only to a short-stroke actuator. The patterning device MA and the substrate W may be aligned using the patterning device alignment marks M1 and M2 and the substrate alignment marks P1 and P2. Although the illustrated substrate alignment marks occupy dedicated target portions, they may be located in spaces between the target portions (they are known as scribe-lane alignment marks). Similarly, in situations in which more than one die is provided on the patterning device MA, the patterning device alignment marks may be located between the dies.

The illustrated device can be used in at least one of the following modes:

1. In the step mode, the support structure MT and the substrate table WT are basically kept stationary, while the entire pattern imparted to the radiation beam is projected onto the target portion C at once (i.e. Single static exposure]. After that, the substrate table WT is shifted in the X and/or Y directions so that different target portions C can be exposed. In the step mode, the maximum size of the exposure field limits the size of the target portion C imaged in a single static exposure.

2. In the scan mode, the support structure MT and the substrate table WT are scanned synchronously while the pattern imparted to the radiation beam is projected onto the target portion C (that is, a single dynamic exposure). )]. The speed and direction of the substrate table WT relative to the support structure MT may be determined by the enlargement (reduction) and image reversal characteristics of the projection system PS. In the scan mode, the maximum size of the exposure field limits the width (in the unscanned direction) of the target portion in a single dynamic exposure, while the length of the scanning operation determines the height (in the scanning direction) of the target portion.

3. In another mode, the support structure MT is kept essentially stationary by holding the programmable patterning device, while the pattern imparted to the radiation beam is projected onto the target portion C, while the substrate table WT ) Is moved or scanned. In this mode, a generally pulsed radiation source is employed, and the programmable patterning device is updated as needed after every movement of the substrate table WT, or between successive radiation pulses during a scan. This mode of operation can be readily applied to maskless lithography using a programmable patterning device such as a programmable mirror array of the type as mentioned above.

Further, combinations and/or variations of the above-described modes of use, or completely different modes of use may be employed.

Although reference is made herein to specific examples of use of a lithographic apparatus in IC manufacturing, the lithographic apparatus described herein is an integrated optical system, a guide and detection pattern for magnetic domain memory, a liquid crystal display (LCD), a thin film magnetic head, and the like. It should be understood that there may be other applications such as manufacturing. Those of ordinary skill in the art, in connection with these alternative applications, that any use of the terms "wafer" or "die" herein may be considered synonymous with the more general terms "substrate" or "target part", respectively. I will understand. The substrate referred to herein may be processed before and after exposure, for example in a track (typically a tool that applies a layer of resist to the substrate and develops the exposed resist), or a metrology or inspection tool. If applicable, the description of this specification may apply to such substrate processing tools and other substrate processing tools. In addition, since the substrate may be processed more than once to produce a multilayer IC, for example, the term substrate as used herein may refer to a substrate including layers that have already been processed several times.

As used herein, the terms “radiation” and “beam” refer to particle beams such as ion beams or electron beams, as well as ultraviolet (UV) radiation (e.g., having a wavelength of 365, 248, 193, 157 or 126 nm). ) Radiation and extreme ultraviolet (EUV) radiation (eg, having a wavelength in the range of 5 to 20 nm).

The various patterns on or provided by the patterning device may have different process windows, i.e., a space of process variables for which the pattern will be created within specification. Examples of pattern specifications related to potential systemic defects include necking, line-end pull back, line thinning, CD, edge placement, overlapping, resist top loss. top loss), resist undercut and/or bridging. The process window of all patterns on the patterning device or its area can be obtained by merging (eg, overlapping) the process windows of each individual pattern. The boundaries of the process windows of all patterns include the boundaries of some of the individual patterns. In other words, these individual patterns limit the process window of all patterns. These patterns may be referred to as “hot spots” or “process window limiting patterns (PWLPs)”, which are used interchangeably herein. When controlling part of the patterning process, it is possible and economical to focus on hot spots. If the hot spots do not cause defects, it is likely that not all of the patterns cause defects.

As shown in Fig. 2, the lithographic apparatus LA may sometimes form a part of a lithographic cell LC, also referred to as a lithocell or cluster, which is pre-exposure and post-exposure on a substrate. It includes devices that perform (post-exposure) processes. Typically, these are one or more spin coaters (SC) that deposit one or more layers of resist, one or more developers (DE) to develop the exposed resist, one or more chill plates (CH) and/or Includes one or more bake plates (BK). A substrate handler or robot (RO) picks up one or more substrates from input/output ports (I/O1, I/O2), moves them between different process units, and loads the lithographic apparatus's loading bay (LB) To pass. These devices, often collectively referred to as tracks, are controlled by a track control unit (TCU), which is self-controlled by a supervisory control system (SCS) that controls the lithographic apparatus via a lithographic control unit (LACU). Thus, different devices can be operated to maximize throughput and processing efficiency.

In order for the substrate to be exposed by the lithographic apparatus to be correctly and consistently exposed, and/or a patterning process (e.g., a device manufacturing process) comprising at least one pattern transfer step (e.g., an optical lithography step) ), to monitor some of the alignment, overlay (e.g., which may be between structures in the same layer or structures in overlapping layers, provided separately in a layer by a double patterning process), line thickness, critical dimension It is desirable to inspect a substrate or other object to measure or determine one or more properties such as (CD), focus offset, material properties, and the like. Thus, the manufacturing facility in which the lysocell LC is located typically also includes a metrology system MET that measures some or all of the substrates W processed in the lysocell or other objects within the lysocell. The metrology system MET may be part of the lithographic apparatus LC, for example it may be part of the lithographic apparatus LA (such as the alignment sensor AS).

The at least one measured parameter is, for example, an overlay between successive layers formed in or on the patterned substrate, for example the critical dimension (CD) of features formed in or on the patterned substrate (e.g., critical line width). ), a focus or focus error in the optical lithography step, a dose or dose error in the optical lithography step, optical aberrations in the optical lithography step, and the like. This measurement can be performed on a target of the product substrate itself and/or a designated metrology target provided on the substrate. The measurement may be performed after development of the resist and before etching, or may be performed after etching.

Various techniques exist, including the use of scanning electron microscopy, image-based measurement tools, and/or various special tools to perform measurements of structures formed during the patterning process. As previously described, there are special metrology tools in the form of high speed and non-invasive, in which a beam of radiation is directed onto a target on the surface of the substrate and the properties of the scattered (diffracted/reflected) beam. Are measured. By evaluating one or more properties of the radiation scattered by the substrate, one or more properties of the substrate may be determined. This can be referred to as diffraction-based metrology. One such application of this diffraction-based metrology is the measurement of feature asymmetry within a target. This can be used, for example, as a measure of the overlay, and other applications are known. For example, asymmetry can be measured by comparing opposite portions of the diffraction spectrum (eg, by comparing the -1 order and +1 order in the diffraction spectrum of a periodic grating). This can be done as previously described and, for example, as described in US 2006-066855, which is incorporated herein by reference in its entirety. Another application of diffraction-based metrology is the measurement of feature width (CD) in a target. These techniques can use the apparatus and methods described below.

Thus, in a device fabrication process (eg, a patterning process or a lithographic process), a substrate or other objects may undergo various types of measurements during or after the process. Measurements can determine if a particular substrate is defective, or establish adjustments to the process and devices used in the process (e.g., aligning two layers on a substrate or aligning a patterning device to a substrate). , It may measure the performance of processes and devices, or may be for other purposes. Examples of measurements include optical imaging (e.g., optical microscope), non-imaging optical measurements (e.g., diffraction-based measurements such as ASML YieldStar metrology tool, ASML SMASH metrology system), mechanical measurements (e.g. For example, profiling with a stylus, atomic force microscopy (AFM)], and/or non-optical imaging (eg, scanning electron microscopy (SEM)). SMASH (SMart Alignment Sensor Hybrid) system, as disclosed in U.S. Patent No. 6,961,116, which is incorporated herein by reference in its entirety, generates two overlapping and relatively rotated images of alignment markers, and the Fourier transform of the image is A self-referencing interferometer is used that detects the intensities in the pupil plane causing interference, and extracts positional information from the phase difference between the diffraction orders of the two images that appear as intensity fluctuations in the interfered orders.

Metrology results can be provided indirectly or directly to a supervisory control system (SCS). If an error is detected (especially if the inspection can be done fast enough so that one or more other substrates in the batch are still exposed), adjust for subsequent exposure of the substrate, and/or for subsequent exposure of the exposed substrate. This can be done. In addition, it is possible to avoid performing another treatment on a substrate that has already been exposed to a substrate that has been stripped and reworked to improve yield, or is discarded and known to be defective. If only some target portions of the substrate are defective, further exposures can be performed only on good target portions.

Within a metrology system (MET), a metrology device is used to determine one or more properties of a substrate, in particular how one or more properties of different substrates change, or how different layers of the same substrate change from layer to layer. Used to determine. As indicated above, the metrology apparatus may be integrated into a lithographic apparatus LA or a lithographic apparatus LC, or may be a stand-alone device.

To enable metrology, one or more targets may be provided on the substrate. In one embodiment, the target may include a specially designed and periodic structure. In one embodiment, the target is a portion of a device pattern, for example a periodic structure of a device pattern. In one embodiment, the device pattern is a periodic structure of a memory device (eg, a structure such as a bipolar transistor (BPT), bit line contact (BLC), etc.).

In one embodiment, the target on the substrate may include one or more 1-D periodic structures (eg, gratings) printed such that, after development, features of the periodic structure are formed into solid resist lines. In one embodiment, the target comprises one or more 2-D periodic structures (e.g., gratings) printed such that after development, one or more periodic structures are formed from solid resist pillars or vias in the resist. Can include. Alternatively, the bars, pillars or vias may be etched into the substrate (eg, into one or more layers on the substrate).

As technology nodes become smaller and design patterns become more complex, the patterning process inevitably prints undesirable patterns or defects on the wafer. As such, several processes and patterning recipes related to, for example, a pre-OPC process of a patterning process, a defect detection process, a pattern verification process, a retargeting process, etc. need to be improved. For this improvement, thousands of patterns of chips can be evaluated. With node scaling, the design rules that enable design check and retargeting have become very complex, resulting in improved pattern manageability and the emergence of pattern-based rules for pattern identification, for example in OPC applications.

Existing pattern recognition or pattern retrieval approaches allow a user to define the desired pattern as an exact replica of what they expect to find. The desired pattern can be defined as a variable number of degrees of freedom (eg, shape, size, edge roughness, etc.) associated with the features of the pattern so that similar patterns can be searched for in the entire chip layout. When executing the pattern search function and scanning the design layout (interchangeably also referred to as field pattern) for patterns matching the desired pattern (also referred to as a search pattern), existing algorithms determine the number of patterns to be searched. Breaking the inflection point (or threshold) becomes too expensive.

Existing pattern matching methods or algorithms have some limitations, including being overly restrictive in defining a fuzzy pattern (e.g., a search pattern), where the search function is only for all of what you want to find on a full-chip. Detect or scan. Topological differences between the desired search pattern and the field layout pattern are so tightly bound that the user creates additional patterns to compensate for inefficiency and inflexibility in the definition of the search pattern, or the search result due to restrictions related to the definition of the search patterns. Additional conditions or software components must be developed to close the gap in the field.

For example, search algorithms or methods for OPC purposes are considered too slow, especially when the number of patterns increases to, for example, thousands or more, limiting the number of patterns a user can have in a pattern library.

The present invention provides, for example, greater flexibility when searching for similar patterns, the ability to finer control the topology definition (e.g., not limiting a fixed set of features or exact shape and size), and Even a large number of patterns provide improved search capability of pattern search with respect to faster execution than other current approaches.

3A-3C are exemplary pattern definitions (also referred to as conditions or specifications) associated with a search pattern and problems associated with using current tools. In FIG. 3A, a grid-based search is provided, where constraints related to features such as 305, 307, 309, and 311 of a pattern (eg, an E-shaped pattern) are defined for the grid. In addition, the pattern has a boundary 301 that further restricts the search boundaries. This grid-based definition does not have per-edge control over pattern conditions. For example, it is unclear whether condition "A" applies to edge "E1" of feature 309, or to edge "E2" of feature 305. Thus, it is not clear whether the edge E1 should be moved or the edge E2 should be moved during the search process, for example, if the condition "A" indicates a movement or displacement of an edge by a predetermined amount. Thus, when looking for the condition "A" or comparing it with the patterns of the field pattern, the search may lead to inaccurate patterns.

In FIG. 3B, the edges of the pattern (eg, E1 and E2) coincide with the pattern boundary 301, and these edges cannot be moved or are fixed relative to the pattern boundary 301. Moving these edges (eg, E1 and E2) causes a topology change (eg, shape change) within the pattern boundary. For example, if the edge E1 is moved by the amount "C" (exemplary constraint), or the edge E2 is moved by the amount "A", the topology of the pattern changes. These topology changes are not acceptable in existing tools, whereby the search may not be performed or may lead to inaccurate search results. However, the present invention still allows for these topology changes while finding a pattern match between the search pattern and the field pattern.

In Figure 3c, another example of a pattern definition or constraint is shown, where edge E4 of feature 311 is shifted by an amount "A" in the vertical downward direction (along the y-axis), and is collinear with another parallel edge of feature 307. Should be in. However, this limitation is not allowed in existing tools because it causes topology changes.

The present invention discusses several methods of defining flexible search conditions that determine a matching pattern between a search pattern and a field pattern based on the search conditions.

Generally, more than one method involves several steps or processes. For example, the method may involve a first process for setting up a search pattern database. The setting of the search pattern database involves applying different conditions to a plurality of patterns, the conditions including, for example, a relative position between different features of the pattern and a tolerance band corresponding to the relative position.

In one embodiment, the method involves a second process in which a pattern search may be performed in a search space based on a search pattern selected from a search pattern database and conditions associated with the search pattern. In one embodiment, this search pattern may be defined by the user through an interface. The second process derives first candidate patterns that can be further filtered based on the second set of conditions.

In one embodiment, the method involves a third process in which another pattern search may be performed based on the first candidate patterns and the bounding box. The search derives second candidate patterns. Therefore, the search space is gradually reduced, so that a larger number of rule checks (e.g., dimensions, coordinates, edge roughness, edge-to-edge placement) for the second candidate patterns to find an excellent match or an exact match with the search pattern. Etc.) can be performed. As checks are performed on a reduced number of candidate patterns, more accurate search results are obtained in a fast and efficient manner (eg, using less computation time and computation resources).

In one embodiment, the method may involve a fourth process in which a final check may be performed on the second candidate pattern. The final check may involve design rule checks, eg EPE, CD, shape, or other geometric attribute checks to find a good match with the search pattern. Further additional patterns can be found by allowing a flexible pattern search to locate patterns with additional features, whereby the search can find patterns that may not be an exact pattern match with the topology of the search pattern.

In one embodiment, the methods of the present invention describe searching for patterns within a field pattern (eg, design layout) that matches the search pattern. In order to provide an efficient search and obtain reliable search results, appropriate search conditions must be defined. The methods involve defining conditions such as allowable displacements between any two edges, including edges located in any of the pattern layers. Conditions may include edges that are independent of the pattern layer. Conditions can also be defined for the boundary edge of the pattern. If all the edges of the feature (of the search pattern) are constrained to the condition, the amount of results will be less compared to the non-constrained search, so a faster search of the patterns within the desired search space can be performed. Thus, in one embodiment, it may be desirable to define conditions for each edge of a feature, or between edges of a feature. In addition, the method provides increased flexibility in topology matching by allowing polygons and edges that are flexible (eg, movable/scalable within tolerance limits). In addition, the method enables dynamic behavior of the bounding box as a function of what the user is trying to match (eg, a search pattern). Typically, the bounding box is of a fixed-dimensional configuration (i.e., it cannot be resized or resized in shape or size), which identifies locations within the pattern where the feature(s) should not exist (other than the features to be retrieved) define.

In one embodiment, a search for patterns may be performed on a substrate or an image of a substrate to find patterns that satisfy a predetermined search criterion, such as a specific search pattern and conditions (or constraints) associated with the specific search pattern. . In one embodiment, such a search involves topological matching of a specific pattern with patterns on the substrate (eg, an outline of features and matching of relative positions between different features). In the present specification, the terms "substrate pattern", "field pattern", or "search space" may be used interchangeably to refer to a design pattern as an example. However, the present invention is not limited to a design pattern, and a person skilled in the art can apply similar search methods to a search space including an image of a printed substrate or a pattern on a substrate that can be obtained from a simulated pattern of the substrate. In one embodiment, a particular search pattern may include one or more features that are compared to thousands of patterns (or features within) of field patterns, for example. Then, field patterns that satisfy the search criteria are considered candidate patterns for further searching for patterns matching additional search criteria associated with, for example, a bounding box (described later in this specification). Candidate patterns may be referred to interchangeably as "realizable patterns", "search results", "realizable set", or "solution space".

Stepwise search based on different search criteria gradually narrows the search space, leading to faster execution of the search method or algorithm. For example, the methods allow an execution time of N*log(N), while conventional methods have a higher execution time such as ^{N 2} , c ^{N, or more.} Moreover, one or more processes of a search algorithm or method may be distributed based on a distributed architecture across one or more processors (e.g., one or more of the processors 104 of the computer system 100) to process the search more quickly. I can.

4 is an exemplary flow diagram of a method 400 of determining candidate patterns from a set of patterns in a patterning process according to an embodiment. In process P42, the method 400 comprises (i) a set of patterns 401 of the patterning process, (ii) a search pattern 402 having a first feature and a second feature, and (iii) a first of the search pattern. It involves obtaining a first search condition 403 comprising the relative position between the feature and the second feature. The first feature may exist near the second feature (eg, within the region of interest). In one embodiment, the second feature is adjacent to the first feature.

In one embodiment, the set of patterns 401 refers to a space in which a search is performed using patterns and a search pattern corresponding to the patterning process. The set of patterns may be interchangeably referred to as "search space" or "field pattern". In one embodiment, the set of patterns may be represented as an image of patterns obtained from a printed substrate and/or simulated patterns on the substrate. In one embodiment, the set of patterns may be extracted from the image of the patterns. In one embodiment, the set of patterns is represented in a search friendly format such as a string or relational database table. In one embodiment, a set of patterns corresponding to the printed substrate is obtained from a scanning electron microscope.

Search pattern 402 is, for example, any pattern of interest intended to be matched with a substrate pattern (e.g., a printed pattern or a simulated pattern) (e.g., a design layout or a design pattern or user- Definition pattern). The search pattern 402 may include a single feature (eg, a contact hole, a bar, a line, etc.) or a plurality of features disposed adjacent to each other. An example of a search pattern is shown in FIG. 9. In one embodiment, the search pattern 402 is a specific search condition (e.g., search condition 403) to enable efficient filtering of potential matching candidates from the search space (e.g., an image of a printed substrate). Is associated with. In one embodiment, the search pattern 402 (eg, design layout) is stored in a database and can be retrieved on demand. In one embodiment, the search pattern 402 may be stored and/or provided in a GDS format or other suitable format for searching.

In one embodiment, the search pattern 402 includes a plurality of features, wherein at least one of the plurality of features is in the same layer of the substrate and/or different layers of the substrate. In one embodiment, the first feature and the second feature are on the same layer. In one embodiment, the first feature and the second feature are on different layers. For example, a first feature (eg, a contact hole) may be in a first layer, and a second feature (eg, another contact hole or bar) may be in a second layer of the substrate. Thus, the method allows for matching patterns that are independent of the layers of the substrate.

Search condition 403 is any condition or constraint associated with one or more features of search pattern 402. For example, the search condition 403 is a condition associated with a first feature of the search pattern and a second feature adjacent to the first feature. In one embodiment, the search condition includes a relative position between elements of the first feature and the second feature of the search pattern. In one embodiment, the relative position may be in a horizontal direction, a vertical direction, and/or an angular direction. In one embodiment, the elements of a feature include edges and/or vertices of the features. In one embodiment, the edge of a feature may be associated with one or more constraints. For example, a first edge of a first feature may be associated with a horizontal constraint with a first edge of a second feature, and a first edge of a first feature with another constraint with a first edge of the third feature. Can be linked. In one embodiment, the search condition 403 may be a distance (eg, 20 nm) between the edge of the first feature and the edge of the second feature.

In one embodiment, the search condition 403 may be a set of conditions associated with a plurality of features of the search pattern, for example, the edge of the first feature and the edge of the second feature of the design pattern. In one embodiment, search pattern 402 may be stored and retrieved from a database (eg, a memory of computer system 100 or a remote server accessible through computer system 100) on demand. Similarly, the search condition 403 can be associated with the search pattern 402 and can be stored and retrieved from the same database. In one embodiment, the search conditions may be in the form of a script (eg, a conditional statement as a Python script), and a processor implementing method 400 may be configured to receive the script.

Additionally or alternatively, the search condition 403 includes a tolerance limit associated with the dimensions of the features and/or the relative position between the elements of the features. The tolerance limit specifies the degree to which the first feature is allowed to move relative to the second feature (or other constrained feature) without deviating from the desired function of the design pattern. Movement of a feature refers to movement (eg, shift or rotation) in a constrained direction (eg, horizontal, vertical, angular, etc.). For example, the distance between the edge of the first feature and the second feature may be 20 nm ± 1 nm in the horizontal direction, thereby causing the edges to move 1 nm with respect to each other.

In process P44, the method comprises a set of patterns that satisfy a search condition associated with a first feature and a second feature of the search pattern 402 through a processor (e.g., process 104 of the computer system 100). It involves determining a first set 404 of candidate patterns from 401.

The first set of candidate patterns 404 are patterns (eg, substrate patterns) in the set of patterns 401 that are topology matching with the search pattern 402 that satisfies the first search conditions. In one embodiment, the first set of candidate patterns 404 is considered a match if the search conditions are satisfied. For example, the search condition 403 may be relative positions between edges of features of a pattern. The first set of such candidate patterns 404 may or may not have a shape, size, inter-edge, or other geometry related match similar to the search pattern. Accordingly, additional condition checks may be performed on the first set of candidate patterns 404 to find matching patterns within the set of patterns 401. The first set of candidate patterns 404 substantially narrows the search space to a subset. For this subset, additional matching, for example, point-to-point matching within a bounding box, shape, size, etc. may be performed to further narrow the search results.

In one embodiment, the patterns in the search pattern 402, the first search condition 403, and the set of patterns 401 may be expressed in a string format that allows string-based comparison and search. In addition, such a string-based search reduces the execution time of the search algorithm or method.

In one embodiment, the features of the search pattern 402 and the candidate pattern (eg, the first or second set of candidate patterns) may be identified through parsing the search pattern and the candidate pattern. In one embodiment, parsing is an algorithm configured to identify objects of interest (eg, features) in a relatively large search space. Upon parsing, a file including information such as location, size, shape, etc. related to the objects of interest may be generated. In addition, the parsed information may be converted from a string through hashing, for example. The string representation of information enables faster comparisons between information (eg, a feature in a search pattern and a feature in a field pattern).

In process P46, the method involves obtaining a bounding box 406 around the search pattern 402 and a second search condition associated with the features of the bounding box 406 and the search pattern 402. In one embodiment, the bounding box 406 may be obtained through a user interface of a drawing tool that allows the user to draw a border (eg, a rectangular shape) around the search pattern 402, for example. In one embodiment, the bounding box may be defined based on the coordinates of the outermost features of the search pattern 402.

In one embodiment, bounding box 406 is defined as a closed boundary around search pattern 402, limiting the search to features within the closed boundary. For example, FIG. 9 illustrates that the bounding box 920 around the features 901, 911, and 913 of the search pattern 900 limits the search to a combination of these features. In one embodiment, during a bounding box based search, patterns with any additional features other than the features of the search pattern (eg, 901, 911 and 913) are considered non-matching patterns and may be ignored.

In one embodiment, the second search condition is any associated with the bounding box 406 (e.g., 920) and one or more features (e.g., 901, 911, and/or 913) of the search pattern 402. It is a condition of han. In one embodiment, the second search condition is associated with a feature in search pattern 402 closest to bounding box 406. In one embodiment, the second search condition includes a relative position between the edge of the feature and the edge of the bounding box. In one embodiment, the relative location is the distance and/or angle between the edge of the feature of the search pattern 402 and the edge of the bounding box 406. Alternatively or additionally, the second search condition may also include a tolerance limit associated with the relative position between the elements of the features of the bounding box 406 and the search pattern 402. The tolerance limit enables dynamic adjustment of the bounding box 406 to the size of the features of the search pattern. Thus, a match can be found even if certain features (of the search space) are not exactly the same size as the features of the search pattern but are still within the tolerance limits.

In one embodiment, for example in process P47, the bounding box 406 may be configured to dynamically change its size and shape based on conditions defined for the bounding box. Thereafter, a search may be performed based on this dynamically modified bounding box. For example, there is a first condition associated with a first feature and a bounding box, and a second condition associated with a second feature and a bounding box. This dynamic behavior of the bounding box provides increased flexibility (compared to the fixed-bounding box), for example in searching for patterns that do not exactly match the size and shape of the search pattern 402.

In one embodiment, a more flexible search may be performed for conditions associated with bounding box 406. In this flexible search, even if the topology of the search pattern and the substrate pattern are different due to the additional features, patterns having additional features other than the features of the search pattern can also be identified as a matching pattern. In one embodiment, patterns with these additional features may indicate a defect or defect, and such a pattern may be of interest in defect identification or classification, for example. Exemplary results of this search are described and discussed with reference to FIG. 13.

In process P48, the method further comprises, via a processor (e.g., process 104 of computer system 100), a first set of candidate patterns 404 that satisfy a second search condition associated with bounding box 406. And determining a second set of candidate patterns 408 from ).

In one embodiment, determining the second set of candidate patterns 408 includes comparing one or more parameters of the features of the search pattern 402 with corresponding one or more parameters of the features of the set of patterns 401; And based on the comparison, selecting a subset of patterns from the first set of candidate patterns 404 excluding patterns with topology mismatch. Topology mismatch refers to patterns with features that are similar to or do not have an exact shape as features in a search pattern. For example, a pattern with an additional feature between two features of the search pattern can be excluded because the additional feature changes the topology of the search pattern.

In one embodiment, the one or more parameters include at least one of: the edge of the feature, the size of the feature, and the topology of the feature. For example, the parameter may be a geometric parameter such as the edge length of the feature of the search pattern, the edge roughness of the feature, and the CD of the feature, and may be compared with parameters corresponding to the feature of the field pattern. The comparison may involve computing the difference between the parameters of the two features and determining whether the difference breaks through a threshold (eg, greater or less than this). In response to a difference that does not break through the threshold, it is said that a match between the search pattern and the field pattern is found, otherwise no match is found.

As mentioned above, the bounding box 406 may have a dynamic behavior in which the size and/or shape of the bounding box 406 may be modified/adjusted. In one embodiment, determining the second set of candidate patterns 408 comprises adjusting the bounding box 406 around the search pattern 402 based on the size of the feature in the second search condition, and the adjusted And determining a second set of candidate patterns 408 from the first set of candidate patterns 404 from the set of patterns 401 that satisfy a second search condition associated with the bounding box. In one embodiment, the step of adjusting the bounding box is limited by the first search conditions, the second search condition, and/or the tolerance limit associated with the parameter of the feature.

In one embodiment, adjusting the bounding box 406 includes increasing and/or decreasing the size of the bounding box relative to the size of the feature of the field pattern. In one embodiment, the amount of increasing and/or decreasing the size of the bounding box is within a tolerance limit associated with the relative position between the bounding box and the elements of the feature.

Also, as mentioned above, the search pattern 402 may include a plurality of features. The plurality of features may be in the same layer of the substrate or different layers of the substrate. In one embodiment, when performing a comparison (e.g., within a bounding box) between the search pattern and the field patterns, only features of the search pattern are compared, while the space between the features may be considered to be empty. . As such, when an additional feature exists between the features of the search pattern 402, the part of the field pattern may be regarded as a mismatch with the search pattern or not as a match.

5 is another exemplary flow chart of a method of determining a matching pattern. In process P52, the method 500 comprises: (i) a selection of candidate patterns from a set of patterns (e.g., 401) based on a first search condition associated with the features of the search pattern (e.g., 402). Obtaining one set 502, (ii) a bounding box 503 around the search pattern, and (iii) a second search condition 504 associated with the features and bounding boxes of the search pattern.

In one embodiment, obtaining the first set of candidate patterns 502 involves configuring a processor (eg, 104) to receive the patterns 502. In one embodiment, the first set of candidate patterns 502 is generated at a different processor in a manner similar to that discussed for process P44 of method 400 above, and transmitted over the network to a process (e.g., 104). Can be. Also, a bounding box 503 (similar to the bounding box 406) can be obtained in process P46 as discussed above. Further, the second search conditions 504 may be obtained through an interface configured to input constraints for, for example, a search pattern (e.g., 900 in FIG. 9) and a bounding box 503 around the search pattern. . The second search conditions 504 are similar to those discussed in method 400 above.

Further, in process P52, the method 500 determines a second set of candidate patterns 508 from the first set of candidate patterns based on a second search condition through a processor (eg, processor 104). It entails the step of doing. In one embodiment, process P52 is similar to process P48 discussed above. An example of such a search is described with reference to FIGS. 10 to 12, which are discussed later in the present invention.

In one embodiment, determining the second set of candidate patterns 508 includes comparing one or more parameters of a feature of the search pattern with a corresponding one or more parameters of the feature of the set of patterns; And based on the comparison, selecting a subset of patterns from the first set of candidate patterns 502 excluding patterns with topology mismatch. In one embodiment, the comparison involves comparing at least one of: the edge of the feature, the size of the feature, and the topology of the feature, as previously discussed at P48. In one embodiment, the selection of a subset is based on this comparison between edge, size, topology and/or other factors such that patterns with feature characteristics similar to the search pattern are selected. In an embodiment, the selected patterns may or may not exactly match the search pattern.

6 is another exemplary flow diagram of a method 600 of determining a matching pattern. Similar to methods 400 and 500, method 600 also involves determining a first set of candidate patterns and a second set of candidate patterns based on respective search conditions. Further, the method 600 enables a search for patterns having additional features other than the features of the search patterns within the bounding box. As such, the method of 600 can provide additional patterns as search results even if these patterns do not have topology matching. Such a flexible search is highly desirable, for example to allow improved optical proximity corrections (OPC).

In process P62, the method 600 includes (i) a selection of candidate patterns from a set of patterns (e.g., 401) based on a first search condition associated with the features of the search pattern (e.g., 402). It involves obtaining one set 602, (ii) a bounding box 603 around the search pattern, and (iii) a second search condition 605 associated with the features and bounding boxes of the search pattern.

In process P64, the method 600 involves determining a second set of candidate patterns 608 from the first set of candidate patterns 602 based on a second search condition, wherein a second set of candidate patterns Set 608 includes candidate patterns with additional features not included in the search pattern. Exemplary search results are described with reference to FIG. 13, which is discussed later in the present invention.

In one embodiment, determining the second set of candidate patterns includes comparing one or more parameters of a feature of the search pattern with a corresponding one or more parameters of a feature of the set of patterns; And, based on the comparison, selecting patterns from the first set of candidate patterns without excluding patterns with topology mismatching. Thus, method 600 differs from methods 400 and 500 as it allows the user to detect additional patterns. In one embodiment, this method may be used for defect detection and/or prevention in cases where additional features may constitute a defect.

In one embodiment, the additional feature may be defined as any feature within the bounding box that is adjacent or in contact with the feature of the search pattern. In one embodiment, the additional features are on the same layer or different layers as the feature in the search pattern. In one embodiment, the additional feature is not associated with constraints on the features of the bounding box or search pattern. Accordingly, according to an embodiment, the search result includes a pattern that is not associated with the search condition (eg, the first search condition or the second search condition).

Also, as mentioned above, the search pattern may include a plurality of features. In one embodiment (e.g., method 400 and method 500), when performing a comparison (e.g., within a bounding box) between a search pattern and field patterns, only features of the search pattern are compared, while features The spaces between them can be considered empty. As such, when there are additional features between features of the search pattern, that part of the field pattern may be regarded as a mismatch with the search pattern or not as a match. However, in one embodiment, the method 600 makes it possible to identify portions on the field pattern with additional features as matching the search pattern. In addition, one of ordinary skill in the art will appreciate that this flexible search may be implemented in other methods such as methods 400 and 500 without limiting the scope of the invention.

7 is an exemplary flow diagram for a method 700 of determining a matching pattern. In process P72, the method 700 involves applying a first search condition between a first feature and a second feature of a search pattern (eg, 402) via a user interface. In one embodiment, applying the first search condition comprises selecting an edge of a first feature and an edge of a second feature of the search pattern, allocating a distance between the selected edges, and/or the selected edges. And assigning a tolerance limit to the distance between them. 9 shows an example of applying a first search condition such that a distance _{of d 1} ±Δd ₁ is allocated between the edges of the feature 901 and the feature 911 _{, where Δd 1} is a tolerance limit for the distance d _1. In another example, a distance d ₂ ±Δd ₂ is assigned between feature 911 and feature 913, where Δd ₂ is the tolerance limit for the distance d _2.

In one embodiment, applying conditions involves defining conditional statements in software between different features of the search pattern. _{For example, the distances d 1} and d ₂ between the edges of the aforementioned features can be expressed as conditional statements, which can be further used in the program to determine whether these conditional statements are satisfied or not. In one embodiment, the conditional statement is defined as a conditional statement based on user input through an interface configured through other interactive functions for displaying a search pattern, selecting features and elements of the search pattern, or defining conditions/constraints. Or can be converted. In one embodiment, these conditions may also be applied/defined through an application programming interface (API), which may be a Python script API.

In one embodiment, the user may for example select two edges and provide a tolerance limit (ie, minimum and maximum difference) between the selected edges. For example, a first edge of a first feature and a first edge of a second feature may be selected within the search pattern. The distance between the edges can then be assigned with the allowable minimum and maximum variation of the distance between the selected edges. Similarly, a distance (eg, CD) between two edges of the same feature can be defined. In addition, these distances and tolerance limits serve as search conditions, where the field pattern is scanned for patterns that satisfy this distance and tolerance limit.

In process P74, the method 700 involves determining a first set of candidate patterns 704 from the set of patterns based on a first search condition. In one embodiment, the first set of candidate patterns 704 is an example of the candidates 402, 502, or 602 discussed above. Determination of the first set of candidate patterns 706 is similar to process P44 of method 400.

Further, in process P76, the method 700 involves drawing a bounding box 706 around the search pattern. In one embodiment, bounding box 706 is an example of bounding box 503 or 603 discussed above. Another example of a bounding box 706 such as 920 is shown in FIG. 9. In one embodiment, the bounding box 706 may be obtained as user input, a script readable by a computer program, or other ways of representing information. In one embodiment, bounding box 706 is drawn by the user through a user interface around the search pattern. For example, in FIG. 9, the user draws a rectangular bounding box 920 around features 901, 911 and 913. This bounding box 920 provides a structure defining additional constraints to be defined to further filter the pattern from the first set of candidate patterns.

In process P78, the method 700 involves applying a second search condition between a bounding box and a first feature or a second feature. In one embodiment, the second search condition may be applied in a manner similar to the first search condition discussed in process P72.

In process P80, the method 700 involves determining a second set of candidate patterns 750 from the first set of candidate patterns based on a second search condition, wherein the second set of candidate patterns is searched. Include candidate patterns with additional features not included in the pattern. In one embodiment, process P80 is similar to process P64 discussed above.

In one embodiment, the search patterns used in the methods 400, 500, 600 and 700 may be generated according to the method 800 discussed below, for example a network or the methods 400 to 700. ) Can be stored in a database to be accessed through other data retrieval techniques during execution of the processes.

8 is an exemplary flow diagram of a method of creating a search pattern database. In process P82, the method involves obtaining a set of patterns 802. In one embodiment, the pattern of the set of patterns 802 includes a plurality of features. In one embodiment, the set of patterns 802 comprises a plurality of patterns, eg, a first pattern having a first plurality of features and a second pattern having a second plurality of features. The set of patterns 802 may be a design pattern, a user-defined pattern, or any other pattern, such as patterns that occur frequently in the process or patterns that occur less frequently, such as defects.

Further, process P84 involves applying a set of conditions 803 (also referred to as constraint) to the set of patterns to generate a set of search patterns, where the search pattern is a set of patterns 802 associated with the search condition. ) Within the pattern. In one embodiment, conditions 803 may be applied in a manner similar to that discussed in process P72 of method 700. In one embodiment, the set of conditions 803 is a first set of conditions associated with a first pattern of a plurality of conditions 803, for example a set of patterns 802, a first set of patterns 802. A second set of conditions associated with the 2 pattern, and the like. As such, there is a possibility that one or more conditions 803 are similar or different to cause a collision.

After assigning the conditions, process P86 involves evaluating whether there is a conflict between one or more search conditions associated between different patterns. For example, it is a collision between one or more features of a first search pattern and one or more features of a second search pattern. This collision check ensures that there are consistent and unique conditions across different patterns. Those skilled in the art can understand that not each pattern of the set of patterns can be printed on a substrate, as such, not all of the patterns of the set of patterns 802 can be found in the substrate pattern (or field pattern).

In one embodiment, evaluating a collision may include identifying one or more features having the same search condition, or identifying whether the search conditions exceed a predetermined threshold of a pattern of a set of patterns; And displaying the identified features having conflicting conditions.

Further, process P88 involves creating and storing a set of search patterns and associated search conditions for which there is no conflict. This set of search patterns constitutes a database of search patterns. One or more patterns can be selected and retrieved from the database to perform a search for the field pattern.

9 is an example of a search pattern 900 having a plurality of features 901, 911, and 913. As mentioned above, the features may be located on the same or different layers of the substrate and do not limit the scope of the invention. In one embodiment, features may be located in the first layer and/or the second layer of the substrate. For example, a first layer includes a first feature 901 and a second layer includes a first feature 911 and a second feature 913. In one embodiment, the first constraint or first set of conditions may include one or more distances between features 901, 911, and 913. For example, the distances d ₁ and d ₂ may be a first set of constraints or conditions between features. Also, tolerance limits can be assigned to one or more distances, such as _{Δd 1} and Δd _2. Moreover, the first set of conditions may include a CD of a feature, such as a CD of feature 913 that is 48 nm; In addition, tolerance limits can be assigned such as ±5 nm. In one embodiment, this search pattern with a first set of conditions can be stored in a database and can be selected for the database on demand.

In one embodiment, the search pattern may be surrounded by bounding box 920. The bounding box 920 may be drawn so that the bounding box 920 surrounds the features 901, 911, and 913. In one embodiment, the bounding box may be defined per layer. Also, a second set of constraints or conditions may be defined for bounding box 920. According to the second set of conditions, the bounding box increases in size such as length (eg, along the x-direction or horizontal direction), and/or height (eg, along the y-direction or vertical direction). Or it can be automatically adjusted to decrease. In one embodiment, if there are no constraints assigned to the height or length, the bounding box can be automatically adjusted to a suitable size, such as 1.2 times, 1.5 times, 2 times, etc. of the original drawn size.

In one embodiment, additional processing may be performed to convert information related to the preceding pattern (eg, size, position, condition, etc.) into a machine-readable format such as conditional statements, Python scripts, and the like. This machine-readable format makes it possible to search, compare, match, and/or determine relevant matching patterns within a search space, such as field pattern 1000 (of FIG. 10). In one embodiment, search pattern 900 and field pattern 1000 are exemplary visual representations of patterns used to describe concepts of the present invention. The format of the patterns 900 and 1000 does not limit the scope of the present invention.

10 is an example of a field pattern 1000 or a printed substrate pattern. The field pattern 1000 includes a plurality of features, such as features 1020 having sub-features 1021, 1022, 1023, 1025, 1026, and 1027 formed on a first layer. In one embodiment, the field pattern may be a substrate pattern obtained in the form of an image (eg, an SEM image) or another data format (eg, a character string) representing patterns on a substrate.

In one embodiment, the first set of candidates may be determined based on the first set of conditions defined in FIG. 9. For example, the processor specifically has features 901, 911, and 913, while searching for patterns similar to the search pattern that satisfy the first set of conditions (as discussed in methods 400-700). Can be configured. Then, field patterns satisfying the first set of these conditions are extracted, leading to a reduced search space, e.g., to area 1005. In one embodiment, the features 1021, 1022, 1023, 1025, 1026, 1027 have different sizes compared to the feature 913 of the search pattern, but such a field pattern is, for example, relative to adjacent patterns. Satisfies the first set of conditions in terms of values and corresponding tolerance limits.

Once the first set of patterns is obtained, a second set of patterns may be determined based on the bounding box and the second set of constraints, as discussed with reference to FIGS. 11A, 11B, 12 and 13. The following description of the steps/processes is merely exemplary and does not limit the scope of the invention. One of ordinary skill in the art may modify the steps as discussed in methods 400-700, for example, to obtain a second set of candidate patterns.

11A and 11B are snapshots of results of intermediate steps involved in determining a second set of candidate patterns from a field pattern matching the search pattern. In an embodiment, a bounding box may be created around one or more patterns of a field pattern similar to the search pattern. In one embodiment, a first bounding box 1101 is created around patterns 1013, 1030, and 1021. A second bounding box 1102 is created around the patterns 1013, 1030, and 1022. A third bounding box 1103 is created around the patterns 1013, 1030, and 1023.

One or more patterns have been identified as the first set of patterns as discussed above. Within bounding boxes, a unique mapping may be established in which each feature (or polygonal shape) of the search pattern is mapped to a field pattern (or polygonal shape). The bounding box may or may not be the same as defined in FIG. 9. For example, features 901, 911, and 913 are mapped to 1013, 1030, and 1021 (or 1022, and 1023).

These bounding boxes (along with the second set of conditions) further reduce the search space, improving computation time during search, matching, and comparison operations, since a relatively smaller number of objects from the field pattern are evaluated. This reduced search space makes the program efficient, especially considering the fact that it can potentially evaluate millions of patterns. Thus, the present methods result in faster execution of pattern search with fewer computational resources.

Bounding boxes 1101, 1102, and 1103 may be the same size or different sizes. In one embodiment, the bounding boxes are separated from each other and do not overlap. In Fig. 11A, the bounding boxes 1101, 1102, and 1103 are made of similar sizes and shapes, but the bounding boxes 1101, 1102, and 1103 have field patterns such as 1021, 1022, and 1023, respectively. Not centered. In one embodiment, the height of the bounding boxes is not adjustable/limited, whereby the height of the bounding boxes may be different from that defined in FIG. 9. In a later process, these bounding boxes may be adjusted based on the bounding box 900 of FIG. 9 and the second set of conditions/constraints defined between the features of the search pattern.

In one embodiment, the process (e.g., P48, P54, P64 or P80 of methods 400-700) places bounding boxes 1101, 1102, and 1103 around field patterns of the first set of candidate patterns. It can be configured to be fixed. Anchoring refers to establishing the reference position of the bounding box with respect to the pattern of the field pattern. For example, FIG. 11B illustrates that the bounding boxes are fixed relative to the center of the patterns 1021, 1022, and 1023 as a reference or set point. Once the fixation is established, the bounding boxes 1101, 1102, and 1103 are shifted relative to this reference position to provide a search space in which further filtering of the patterns of the field pattern can be performed, as shown in Fig. 11B.

Bounding boxes 1101, 1102, and 1103 (in FIGS. 11A and 11B) are not associated with height (or y-direction) constraints, so these boxes are not constrained in the y-direction, but the pattern in the field pattern It may be adjusted or limited in the x-direction (or horizontal direction) according to the size of the units. Also, a second set of constraints can be applied to the bounding box to further reduce the search space of the field pattern. For example, bounding boxes may be resized, and further evaluation may be performed to determine whether second conditions for features of the search pattern are satisfied.

12 shows an exemplary adjustment of the bounding boxes of FIGS. 11A and 11B. In FIG. 12, bounding boxes 1201, 1202 and 1203 are scaled versions of bounding boxes 1101, 1102, and 1103, respectively. In one embodiment, the adjustment may be performed according to the process discussed in methods 400-700. In one embodiment, the adjustment of the bounding box may be based on the size of the feature within the bounding box, and/or a second condition (eg, the distance between the bounding box and the edge of the feature). For example, features 1021, 1022 and 1023 are made of different sizes (eg, CD values are 45 nm, 48 nm and 64 nm, respectively). Thus, the bounding boxes 1201, 1202, and 1203 are adjusted according to the size of the patterns 1021, 1022, and 1023, respectively. Additionally (or alternatively), the adjustment may be based on constraints. _{For example, the first bounding box 1201 is the distance d 3} and d ₄ (and its corresponding tolerances) between the features (e.g., 901 and 913) of the search pattern 900 (defined in FIG. 9). Limits). Adjustment may involve adjustment of the width and/or height of the bounding box. _{Similarly, the second bounding box 1202 is the distance d 5} and d ₆ (and its corresponding tolerance limits) between the features (e.g., 901 and 913) of the search pattern 900 (defined in FIG. 9). ) Can be adjusted based on. _{Similarly, the third bounding box 1203 is the distance d 7} and d ₈ (and its corresponding tolerance limits) between the features (e.g., 901 and 913) of the search pattern 900 (defined in FIG. 9). ) Can be adjusted based on. In the previous example, upon adjustment, the bounding boxes 1201, 1202, and 1203 each have different sizes, for example 130 nm, 134 nm, and 150 nm, and the heights of each bounding box are the same. Those skilled in the art will appreciate that the invention is not limited to the preceding illustration or the aforementioned adjustment, and that any other adjustment may be determined based on the second conditions or the first conditions.

In one embodiment, some field patterns within the boundary may not satisfy the second conditions (e.g., distance, tolerance, feature size, etc.), in which case these patterns are regarded as non-matching patterns and search space Is filtered in.

13 is an example of search results in which second candidate patterns include additional features (ie, patterns other than search patterns) in a bounding box. These results can be obtained as discussed in process P80 of method 800. In one embodiment, features within the bounding box may not be accurately mapped to features of the search pattern. For example, additional features 1311, 1312, and 1313 in bounding boxes 1301, 1302, and 1303 may not be mapped to features of the search pattern (e.g., 901, 911, and 913), respectively. have. Additional features are located in empty spaces between different features and are adjacent to one or more features corresponding to the search pattern. Bounding boxes 1301, 1302 and 1303 have additional properties that allow this flexible search to find additional patterns, for example compared to bounding boxes 1101-1103. Thus, depending on the dynamic behavior of the bounding box, different search results can be obtained.

The previous methods have several advantages and provide improvements over the state-of-the-art technology. For example, in one embodiment, the method allows the user to define search conditions to include edges that are independent of the layer (of the substrate). Further, boundary conditions may be defined between the bounding box of the pattern and any edge of the search pattern. Bounding box related conditions are defined such that the bounding box (or even features) can be stretched or contracted by a predetermined amount relative to the criterion that is held fixed in place. For example, the bounding box can stretch horizontally or shrink horizontally. Also, the bounding box (or features within bounding boxes) is allowed to be shifted within a set tolerance limit. Thus, the methods allow edge-by-edge control by applying appropriate conditions between the bounding box and the edges of features. For example, the bounding box should stretch 20 nm for the feature size as well as shift 10 nm for the edge of the feature closest to the bounding box. This flexibility is highly demanded by designers to improve the patterning process through recipe or OPC changes based on the previously discussed search results.

Advanced methods of searching for a desired pattern within a search space such as a design layout or printed substrate are pre-OPC retargeting, verification processes, defect identification and prevention, or other when a pattern with specific specifications is desired to be printed. You can have several applications, including applications.

In one embodiment, the preceding methods may be used in the pre-OPC retargeting process. Typically, the retargeting process involves adjusting the edges of the pattern in the design layout to account for variations in resist, etching and/or other processes in the patterning process. For example, compared to the target specification, the size of a square or contact hole may be increased, and the line may be slightly wider. In one embodiment, the retargeting process includes width, space, y nm width (e.g., y = 15 nm, 20 nm, 30 nm, ...), y nm space (e.g., y = 5 nm, 7 nm). , 10 nm, …), etc., if certain edges are found, a certain amount (eg, within tolerance limits) so that the desired patterns are printed more accurately (eg, closer to the target specification). It is a global process where it may be desirable to move these feature elements (eg, edges) as many times as possible. In one embodiment, the movement of these edges may be table based, which entails many two dimensions in the design (eg, distance/width/height in x-direction and y-direction). Rules for moving edges may be in the form of tables that become complex multi-dimensional tables, and the present methods enable efficient execution and check of rules in parallel in multiple tables. In very complex areas of the design pattern or substrate pattern, retargeting (eg, adjustment to the edges) may not be applied correctly. However, considerable effort is required to revalidate or update a retargeting recipe that must be fitted to a specific local area with complex patterns. With these methods, a specific pattern (eg, search pattern 900) may be searched to find retargeting error areas. The method allows the user to fuzzy up (eg, change feature relationships/positions within tolerance limits) a particular pattern in a way that allows the user to find the retargeting related pattern in the next or different design. If a pattern is found in the next design, a "pass through" operation can be performed. The pass-through operation involves storing patterns of different layers (e.g., retargeting patterns/modification), for example the pattern may be stored as part of the first layer for retrieval purposes, and the second The layer may contain the final solution after defining the retargeting recipe. In one embodiment, a search using a fuzzy pattern may involve additional post-processing of matching results (ie, patterns at matching locations) at matching locations after identifying retargeting locations. In one embodiment, the further treatment is, for example, applying certain retargeting or biasing edges, and/or blocking the pattern with the pattern of the pass-through layer (e.g., the first layer). It can entail. Thus, the above methods better cover the current field pattern and help to properly direct the user to the patterns and their locations where the retargeting recipe has failed.

In one embodiment, the methods of the present invention may be used for pattern verification. Often, after a process simulation is performed to predict patterns such as a substrate or OPC patterns, verification is performed on a desired pattern or pattern on a design layout to identify patterns with defects.

Further verification of the predicted defect patterns can be performed on the printed substrate via a metrology tool (eg, SEM). The metrology tool may or may not find these defects, or other defects outside the range of the patterns identified in the verification process. Missing certain defects in the verification process can be problematic because these missed defects can be printed on the substrate and process models used during the simulation and verification process may not be covered. In one embodiment, it may be desirable to adjust process parameters or process flow without the need to change the process model or change the process recipe. This is because these adjustments are time-consuming and labor-intensive to obtain different model recipes. Thus, a pattern of defects identified from a metrology tool (eg, an SEM image) can be patterned (eg, converted into a search pattern). During patterning of the defect patterns (identified by data from the metrology tool), the defect pattern can be tailored by additional conditions (e.g., relative position, tolerance limit, etc.) This can be used as a search pattern. Such an additional search pattern may be included in the verification process, and the verification process may be supplemented with an additional pattern search.

In one embodiment, the methods can be used to prevent defects. During the fab's patterning process, two types of inspections can be performed on the wafer. Firstly, guided inspection in a database or wafer die via an inspection tool (e.g., SEM) can result in defects (e.g., signal mismatch between desired pattern image and wafer pattern image) and flag pattern ( flag patterns) or locations with defects. This flagging is usually a good indicator of what will happen to the next die or next wafer. Thus, even if these defect patterns may be outside the simulation-based pattern, the verification process will find it. While some of these simulation-based defect patterns may be nuisance or false defects (e.g., 40% or 50% of the identified defects may be false, or are not apparent in wafer defects), some These are borderline defects or substantial defects. Thus, the methods can be used to further use the search patterns to create a search for these defect patterns and to identify locations on the wafer that may fail. After that, appropriate defect prevention measures such as OPC and retargeting can be taken.

As mentioned above, inspection of semiconductor wafers, for example, is often done with optical-based resolution sub-tools (bright-field inspection). However, in some cases, certain features to be measured are too small to be effectively measured using bright-field inspection. For example, bright-field inspection of defects in features of a semiconductor device can be difficult. Moreover, as time progresses, features fabricated using patterning processes (eg, semiconductor features fabricated using lithography) are getting smaller, and in many cases the density of features is also increasing. Therefore, a higher resolution inspection technique is used and required. An exemplary inspection technique is electron beam inspection. Electron beam inspection involves focusing an electron beam on a small spot on the substrate to be inspected. The image is formed by providing relative movement between the beam and the substrate over the area of the substrate being inspected (hereinafter referred to as scanning the electron beam) and collecting secondary and/or backscattered electrons with an electron detector. The image data is then processed to identify defects, for example.

Thus, in one embodiment, the inspection apparatus produces an image of a structure (e.g., part or all of a structure of a device such as an integrated circuit) that is exposed or transferred onto a substrate (e.g., a scanning electron microscope (SEM)). ) And may be an electron beam inspection device.

14 schematically shows an embodiment of an electron beam inspection apparatus 200. After the primary electron beam 202 emitted from the electron source 201 is converged by the condensing lens 203, it passes through the beam deflector 204, the E x B deflector 205, and the objective lens 206 to focus. At, the substrate 100 on the substrate table 101 is irradiated.

When the substrate 100 is irradiated with the electron beam 202, secondary electrons are generated from the substrate 100. The secondary electrons are deflected by the E x B deflector 205 and detected by the secondary electron detector 207. For example, with the continuous movement of the substrate 100 by the substrate table 101 in the other direction of the X or Y direction, the electron beam 202 by the beam deflector 204 in the X or Y direction. A two-dimensional electron beam image can be obtained by detecting electrons generated from the sample in synchronization with repetitive scanning or two-dimensional scanning of the electron beam by the beam deflector 204. Thus, in one embodiment, the electron beam inspection device is an angular range in which the electron beam can be provided by the electron beam inspection device (eg, the angular range in which the deflector 204 can provide the electron beam 202) It has a field of view for the electron beam defined by. Thus, the spatial size of the field of view is the spatial size that the angular range of the electron beam can impinge on the surface (where the surface can be fixed or can move relative to the field).

The signal detected by the secondary electron detector 207 is converted into a digital signal by an analog/digital (A/D) converter 208 and the digital signal is transmitted to the image processing system 300. In one embodiment, the image processing system 300 may have a memory 303 that stores all or part of digital images for processing by the processing unit 304. The processing unit 304 (eg, specially designed hardware or a combination of hardware and software or a computer readable medium including software) is configured to convert or process digital images into datasets representing digital images. In one embodiment, the processing unit 304 is configured or programmed to cause execution of the methods described herein. Further, the image processing system 300 may have a storage medium 301 configured to store digital images and corresponding datasets in a reference database. The display device 302 can be connected to the image processing system 300 to enable an operator to perform the necessary operations of the equipment with the aid of a graphical user interface.

15 schematically shows a further embodiment of an inspection device. The system is used to inspect a sample 90 (such as a substrate) on a sample stage 89, a charged particle beam generator 81, a condensing lens module 82, a probe forming objective module 83, and charged particles. A beam deflection module 84, a secondary charged particle detector module 85, and an image forming module 86 are included.

The charged particle beam generator 81 generates a primary charged particle beam 91. The condensing lens module 82 condenses the generated primary charged particle beam 91. The probe formation objective lens module 83 focuses the condensed primary charged particle beam to the charged particle beam probe 92. The charged particle beam deflection module 84 scans the formed charged particle beam probe 92 over the surface of the region of interest on the sample 90 fixed to the sample stage 89. In one embodiment, the charged particle beam generator 81, the condensing lens module 82 and the probe forming objective module 83, or equivalent designs, alternatives or any combination thereof, are combined with scanning charged particles. A charged particle beam probe generator that generates a beam probe 92 is formed.

The secondary charged particle detector module 85 contains secondary charged particles 93 emitted from the sample surface (perhaps with other reflected or scattered charged particles from the sample surface) when impacted by the charged particle beam probe 92. ) Is detected, and a secondary charged particle detection signal 94 is generated. The image forming module 86 (e.g., a computing device) is coupled with the secondary charged particle detector module 85 to receive the secondary charged particle detection signal 94 from the secondary charged particle detector module 85, and thereby At least one scan image is formed accordingly. In one embodiment, the secondary charged particle detector module 85 and the image forming module 86, or equivalent designs, alternatives, or any combination thereof, are impacted together by the charged particle beam probe 92. An image forming apparatus that forms a scan image from the detected secondary charged particles emitted from the receiving sample 90 is formed.

In one embodiment, the monitoring module 87 is coupled to the image forming module 86 of the image forming apparatus to monitor the patterning process using the scanned image of the sample 90 received from the image forming module 86, Control, etc., and/or derive parameters for patterning process design, control, monitoring, etc. Thus, in one embodiment, the monitoring module 87 is configured or programmed to cause execution of the methods described herein. In one embodiment, the monitoring module 87 comprises a computing device. In one embodiment, the monitoring module 87 includes a computer program that provides functionality herein and is encoded on a computer readable medium that forms or is disposed therein.

In one embodiment, such as the electron beam inspection tool of FIG. 14 that inspects the substrate using a probe, the electron current of the system of FIG. 15 is considerably greater compared to, for example, a CD SEM as shown in FIG. 14, The probe spot may be large enough to speed up the inspection. However, the resolution may not be high compared to CD SEM due to the large probe spot. In one embodiment, the inspection apparatus discussed above (of FIG. 13 or 14) may be a single beam or a multi-beam apparatus without limiting the scope of the present invention.

For example, the SEM image from the system of FIGS. 14 and/or 15 may be processed to extract contours that describe the edges of objects representing device structures in the image. Thereafter, these contours are typically quantified through a metric such as CD at a user-defined cut-line. Thus, images of device structures are typically compared and quantified through metrics such as the distance between edges (CD) measured in the extracted contours or simple pixel differences between images.

According to an embodiment, a method of determining candidate patterns from a set of patterns of a patterning process is provided. The method comprises (i) a set of patterns in the patterning process, (ii) a search pattern having a first feature and a second feature adjacent to the first feature, and (iii) a relative position between the first feature and the second feature of the search pattern. Obtaining a first search condition including; And determining, via the processor, a first set of candidate patterns from a set of patterns that satisfy a first search condition associated with the first feature and the second feature of the search pattern.

In one embodiment, the relative position is defined between the element of the first feature and the element of the second feature of the search pattern.

In one embodiment, the element includes an edge and/or vertex of each feature.

In one embodiment, the first search condition further comprises a tolerance limit associated with the dimensions of the features and/or the relative position between the elements of the features.

In one embodiment, the first feature and the second feature are on the same layer.

In one embodiment, the first feature and the second feature are on different layers.

In one embodiment, the method includes: obtaining a bounding box around the search pattern and a second search condition associated with the feature and bounding box of the search pattern; And determining, via the processor, a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the bounding box.

In one embodiment, the second search condition includes a relative position between an edge of the bounding box and an edge of a feature of the search pattern.

In one embodiment, the relative position is the distance and/or angle between the edge of the bounding box and the edge of the feature of the search pattern.

In one embodiment, the second search condition further comprises a tolerance limit associated with the relative position between the bounding box and the element of the feature of the search pattern.

In one embodiment, the second search condition is associated with the feature of the search pattern closest to the bounding box.

In one embodiment, determining the second set of candidate patterns further comprises comparing one or more parameters of the features of the search pattern with a corresponding one or more parameters of the features of the set of patterns.

In one embodiment, the one or more parameters include: edge of the feature; The size of the feature; And at least one of the topologies of the feature.

In one embodiment, determining the second set of candidate patterns includes adjusting a bounding box around the search pattern based on a second search condition; And determining a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the adjusted bounding box.

In one embodiment, adjusting the bounding box includes increasing and/or decreasing the size of the bounding box for increasing and/or decreasing the size of the features of the second search condition and the field pattern.

In one embodiment, the amount of increase and/or decrease in the size of the bounding box is within a tolerance limit associated with the relative position between the bounding box and the elements of the feature in the search pattern.

In one embodiment, the set of patterns is obtained from an image of patterns of a printed substrate and/or simulated patterns of a substrate.

In one embodiment, the set of patterns is obtained from a scanning electron microscope image.

In one embodiment, the search pattern includes a plurality of features, the plurality of features being in the same layer of the substrate and/or different layers of the substrate.

Further, according to an embodiment, a method of determining candidate patterns from a set of patterns is provided. The method comprises (i) a first set of candidate patterns from a set of patterns based on a first search condition associated with features of the search pattern, (ii) a bounding box around the search pattern, and (iii) a feature of the search pattern. And obtaining a second search condition associated with the bounding box. And determining a second set of candidate patterns from the first set of candidate patterns based on the second search condition.

In one embodiment, the second search condition is the distance and/or angle between the edge of the bounding box and the edge of the feature of the search pattern.

In one embodiment, the second search condition further comprises a tolerance limit associated with a distance and/or angle between the bounding box and an element of the feature of the search pattern.

In one embodiment, determining the second set of candidate patterns includes comparing one or more parameters of a feature of the search pattern with a corresponding one or more parameters of a feature of the set of patterns; And based on the comparison, selecting a subset of patterns from the first set of candidate patterns excluding patterns with topology mismatch.

In one embodiment, the one or more parameters include: edge of the feature; The size of the feature; And at least one of the topologies of the feature.

In one embodiment, determining the second set of candidate patterns includes adjusting a bounding box around the search pattern based on a second search condition; And determining a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the adjusted bounding box.

In one embodiment, adjusting the bounding box includes increasing and/or decreasing the size of the bounding box as a function of the size of the feature in the second search condition and the field pattern.

In one embodiment, the amount of increase and/or decrease in the size of the bounding box is within a tolerance limit associated with the relative position between the bounding box and the elements of the feature in the search pattern.

Further, according to an embodiment, a method of determining candidate patterns from a set of patterns of a patterning process is provided. The method comprises (i) a first set of candidate patterns from a set of patterns based on a first search condition associated with features of the search pattern, (ii) a bounding box around the search pattern, and (iii) a feature of the search pattern. And obtaining a second search condition associated with the bounding box. And determining a second set of candidate patterns from the first set of candidate patterns based on the second search condition, wherein the second set of candidate patterns includes a candidate pattern having additional features not included in the search pattern. do.

In one embodiment, the additional features are adjacent to and within the bounding box of the features of the search pattern.

In one embodiment, the additional features are on the same layer and/or on a different layer as the features of the search pattern.

In one embodiment, the additional feature is not associated with a bounding box or constraint on the features of the search pattern.

In one embodiment, determining the second set of candidate patterns includes comparing one or more parameters of a feature of the search pattern with a corresponding one or more parameters of a feature of the set of patterns; And based on the comparison, selecting patterns from the first set of candidate patterns without excluding patterns having topology mismatching.

In one embodiment, the one or more parameters include: edge of the feature; The size of the feature; And at least one of the topologies of the feature.

Further, according to an embodiment, a method of determining candidate patterns from a set of patterns of a patterning process is provided. The method includes applying a first condition between a first feature and a second feature of a search pattern through an interface; Determining, through the processor, a first set of candidate patterns from the set of patterns based on the first constraint; Drawing, via the interface, a bounding box around the search pattern; Applying, via the interface, a second condition between the bounding box and the first feature or the second feature; And determining, through the processor, a second set of candidate patterns from the first set of candidate patterns based on a second condition, wherein the second set of candidate patterns is a candidate having additional features not included in the search pattern. Includes the pattern.

In one embodiment, applying the first condition includes selecting an edge of a first feature and an edge of a second feature of the search pattern; Allocating a distance between the selected edges; And/or assigning a tolerance limit to the distance between the selected edges.

In addition, according to an embodiment, a method of generating a search pattern database is provided. The method comprises obtaining a set of patterns, the pattern of the set of patterns comprising a plurality of features; Applying, via an interface, a set of search conditions to the set of patterns to generate a set of search patterns-the search pattern is associated with the search condition; Evaluating, via the processor, whether there is a conflict between the one or more search conditions associated with the one or more features of the set of patterns; And storing, via the processor, a set of search patterns and associated search conditions for which there is no conflict.

In one embodiment, evaluating a collision includes identifying features of a set of patterns having the same search condition; And/or determining whether the search conditions exceed a preset threshold associated with a feature of the pattern in the set of patterns. And/or displaying the identified features to modify the conditions to eliminate the conflict.

Further, according to an embodiment, there is provided a computer program product comprising a non-transitory computer readable medium having instructions recorded thereon, the instructions implementing the steps of any of the methods described above when executed by a computer.

16 is a block diagram illustrating a computer system 100 that may assist in implementing the optimization methods and flows disclosed herein. The computer system 100 includes a bus 102 or other communication mechanism to convey information, and a processor 104 (or multiple processors 104 and 105) coupled with the bus 102 to process the information. . The computer system 100 also includes a main memory 106 coupled to the bus 102, such as a random access memory (RAM) or other dynamic storage device that stores information and instructions to be executed by the processor 104. do. Further, the main memory 106 may be used to store temporary variables or other intermediate information upon execution of instructions to be executed by the processor 104. Computer system 100 further includes a read only memory (ROM) 108 or other static storage device coupled to bus 102 that stores static information and instructions for processor 104. A storage device 110 such as a magnetic or optical disk is provided and coupled to the bus 102 to store information and instructions.

Computer system 100 may be coupled via bus 102 to a display 112 such as a cathode ray tube (CRT) or flat panel or touch panel display that presents information to a computer user. An input device 114 comprising alphanumeric and other keys is coupled to the bus 102 to convey information and command selections to the processor 104. Another type of user input device transfers direction information and command selections to the processor 104, and provides cursor control such as a mouse, trackball, or cursor direction keys to control cursor movement on the display 112. : 116). This input device typically has 2 degrees of freedom in the first axis (eg, x) and the second axis (eg, y), two axes that allow the device to specify positions in the plane. Also, a touch panel (screen) display may be used as an input device.

According to one embodiment, portions of the processes described herein may be performed by computer system 100 in response to processor 104 executing one or more sequences of one or more instructions contained in main memory 106. have. These instructions may be read into main memory 106 from another computer-readable medium such as storage device 110. Execution of sequences of instructions contained within main memory 106 causes processor 104 to perform the process steps described herein. Further, one or more processors in a multi-processing arrangement may be employed to execute sequences of instructions contained within main memory 106. In an alternative embodiment, hard-wired circuitry may be used in place of or in combination with software instructions. Thus, embodiments are not limited to any particular combination of hardware circuitry and software.

The term "computer-readable medium" as used herein refers to any medium that is involved in providing instructions to processor 104 for execution. Such media can take many forms including, but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical or magnetic disks such as storage device 110. Volatile media includes dynamic memory such as main memory 106. The transmission medium includes wires including the bus 102, and includes a coaxial cable, a copper wire, and an optical fiber. In addition, the transmission medium may take the form of an acoustic wave or a light wave, such as wavelengths generated during radio frequency (RF) and infrared (IR) data communication. Common types of computer-readable media are, for example, floppy disks, flexible disks, hard disks, magnetic tapes, any other magnetic media, CD-ROM, DVD, any Other optical media, punch card, paper tape, any other physical media with a pattern of holes, RAM, PROM, and EPROM, FLASH-EPROM, any other memory chip Or a cartridge, a carrier wave as described below, or any other medium readable by a computer.

Computer-readable media in various forms may be involved in conveying one or more sequences of one or more instructions to processor 104 for execution. For example, instructions may initially be stored on a magnetic disk in a remote computer (bear). The remote computer can load instructions into its dynamic memory and send the instructions over the phone line using a modem. A modem local to the computer system 100 may receive data on the telephone line and use an infrared transmitter to convert the data into an infrared signal. An infrared detector coupled to the bus 102 may receive data transmitted as an infrared signal and place the data on the bus 102. Bus 102 passes the data to main memory 106 where processor 104 retrieves and executes instructions. Instructions received by main memory 106 may be selectively stored in storage device 110 before or after execution by processor 104.

Further, the computer system 100 may include a communication interface 118 coupled to the bus 102. Communication interface 118 couples to a network link 120 that connects to local network 122 to provide two-way data communication. For example, the communication interface 118 may be an integrated services digital network (ISDN) card or a modem that provides a data communication connection to a corresponding type of telephone line. As another example, communication interface 118 may be a local area network (LAN) card that provides a data communication connection to a compatible LAN. Also, a radio link may be implemented. In any such implementation, communication interface 118 transmits and receives electrical, electromagnetic or optical signals carrying digital data streams representing various types of information.

Typically, network link 120 provides data communication to other data devices over one or more networks. For example, the network link 120 may provide a connection through the local network 122 to a host computer 124 or to a data equipment operated by an Internet Service Provider (ISP) 126. In turn, ISP 126 provides data communication services over a worldwide packet data communication network, now commonly referred to as "Internet" Local network 122 and Internet 128 both use electrical, electromagnetic or optical signals to carry digital data streams. Signals over the various networks, and signals on the network link 120 through the communication interface 118 that carries digital data to and from the computer system 100, are exemplary forms of carrier waves that carry information.

Computer system 100 may transmit messages over network(s), network link 120 and communication interface 118, and receive data, including program code. In the Internet example, the server 130 may transmit the requested code for the application program through the Internet 128, the ISP 126, the local network 122, and the communication interface 118. According to one or more embodiments, one such downloaded application provides for example lighting optimization of the embodiment. The received code may be executed by the processor 104 as it is received, and/or may be stored in the storage device 110 or other non-volatile storage for later execution. In this way, the computer system 100 can obtain the application code in the form of a carrier wave.

17 schematically shows another exemplary lithographic projection apparatus LA, which:

-A source collector module SO for providing radiation;

-An illumination system (illuminator) IL configured to condition a radiation beam B (eg EUV radiation) from the source collector module SO;

-A support structure (e.g., a mask table) configured to support a patterning device (e.g. a mask or reticle) MA and connected to a first positioner PM configured to accurately position the patterning device; (MT);

-A substrate table (e.g., a wafer table) configured to hold a substrate (e.g. a resist-coated wafer) (W) and connected to a second positioner (PW) configured to accurately position the substrate (WT); And

-A projection system configured to project a pattern imparted to the radiation beam B by the patterning device MA onto a target portion C (e.g., comprising one or more dies) of the substrate W (e.g. For example, reflective projection system) (PS).

As shown herein, the device LA is of a reflective type (eg employing a reflective mask). It should be noted that, since most materials are absorbent within the EUV wavelength range, the patterning device can have multi-layer reflectors including, for example, a multi-stack of molybdenum and silicon. In one example, the multi-stack reflector has 40 layers of molybdenum and silicon pairs, with the thickness of each layer being a quarter wavelength. Even smaller wavelengths can be produced with X-ray lithography. Because most materials are absorbent at EUV and x-ray wavelengths, a flake of patterned absorbent material on the patterning device topography (e.g., TaN absorber on top of a multilayer reflector) will be printed (positive resist) or not (negative). Resist) defines the location of the features.

Referring to FIG. 17, the illuminator IL receives an extreme ultraviolet radiation beam from the source collector module SO. Methods of generating EUV radiation include, but are not limited to, converting a material with at least one element having at least one emission line within the EUV range, such as xenon, lithium or tin, to a plasma state. In one such method, commonly referred to as laser generated plasma ("LPP"), the plasma can be created by irradiating a fuel such as droplets, streams or clusters of material with line-emitting elements with a laser beam. The source collector module SO may be part of an EUV radiation system including a laser (not shown in FIG. 17) that provides a laser beam to excite the fuel. The resulting plasma emits output radiation, for example EUV radiation, which is collected using a radiation collector disposed in the source collector module. For example, if a CO ₂ laser is used to provide a laser beam for fuel excitation, the laser and source collector module may be separate entities.

In this case, the laser is not considered to form part of the lithographic apparatus, and the radiation beam is passed from the laser to the source collector module, for example with the aid of a beam delivery system comprising suitable directing mirrors and/or a beam expander. . In other cases, for example, if the radiation source is a discharge generating plasma EUV generator commonly referred to as a DPP radiation source, the radiation source may be an integral part of the source collector module.

The illuminator IL may include an adjuster that adjusts the angular intensity distribution of the radiation beam. In general, at least the outer and/or inner radial extent (commonly referred to as σ-outer and σ-inner, respectively) of the intensity distribution in the pupil plane of the illuminator can be adjusted. Additionally, the illuminator IL may include various other components, such as facetted field and pupil mirror devices. The illuminator can be used to condition the radiation beam so that it has a desired uniformity and intensity distribution in its cross-section.

The radiation beam B is incident on a patterning device (eg, a mask) MA, which is held on a support structure (eg, a mask table) MT, and is patterned by the patterning device. After being reflected from the patterning device (e.g., mask) MA, the radiation beam B passes through the projection system PS, which focuses the beam onto the target portion C of the substrate W. . With the aid of the second positioner PW and the position sensor PS2 (for example an interferometric device, a linear encoder, or a capacitive sensor), the substrate table WT is for example the path of the radiation beam B It can be accurately moved to position the different target portions C within. Similarly, the first positioner PM and another position sensor PS1 can be used to accurately position the patterning device (e.g., mask) MA with respect to the path of the radiation beam B. . The patterning device (eg, mask) MA and the substrate W may be aligned using the patterning device alignment marks M1 and M2 and the substrate alignment marks P1 and P2.

The illustrated device LA may be used in at least one of the following modes:

1. In the step mode, the support structure (e.g., the mask table) MT and the substrate table WT are basically held in a stationary state, while the entire pattern imparted to the radiation beam is at once the target portion C ) Is projected onto (i.e., a single static exposure). After that, the substrate table WT is shifted in the X and/or Y directions so that different target portions C can be exposed.

2. In the scan mode, the support structure (eg, the mask table) MT and the substrate table WT are scanned synchronously while the pattern imparted to the radiation beam is projected onto the target portion C (ie , Single dynamic exposure]. The speed and direction of the substrate table WT relative to the support structure (eg, mask table) MT may be determined by the enlargement (reduction) and image reversal characteristics of the projection system PS.

3. In another mode, the support structure (e.g., mask table) MT is kept essentially stationary by holding the programmable patterning device, and the pattern imparted to the radiation beam is placed on the target portion C. The substrate table WT is moved or scanned while being projected to. In this mode, a generally pulsed radiation source is employed, and the programmable patterning device is updated as needed after every movement of the substrate table WT, or between successive radiation pulses during a scan. This mode of operation can be readily applied to maskless lithography using a programmable patterning device such as a programmable mirror array of the type as mentioned above.

18 shows the device LA in more detail, including the source collector module SO, the illumination system IL, and the projection system PS. The source collector module SO is configured and arranged to maintain a vacuum environment in an enclosing structure 220 of the source collector module SO. The EUV radiation emitting plasma 210 may be formed by a discharge generating plasma radiation source. EUV radiation can be produced by a gas or vapor, for example Xe gas, Li vapor or Sn vapor, in which a very hot plasma (210) is generated to emit radiation within the EUV range of the electromagnetic spectrum. The ultra-high temperature plasma 210 is generated, for example, by an electrical discharge resulting in an at least partially ionized plasma. For the efficient generation of radiation, a partial pressure of Xe, Li, Sn vapor or any other suitable gas or vapor may be required, for example 10 Pa. In one embodiment, a plasma of excited tin (Sn) is provided to produce EUV radiation.

The radiation emitted by the ultra-high temperature plasma 210 is an optional gas barrier or contaminant trap 230 (in some cases, a contaminant barrier or foil located within or behind the opening of the source chamber 211). Also referred to as a trap), it is passed from the source chamber 211 into the collector chamber 212. The contaminant trap 230 may include a channel structure. In addition, the contaminant trap 230 may include a gas barrier or a combination of a gas barrier and a channel structure. The contaminant trap or contaminant barrier 230 further described herein comprises at least a channel structure as known in the art.

The collector chamber 212 may include a radiation collector CO, which may be a so-called grazing incidence collector. The radiation collector CO has an upstream radiation collector side 251 and a downstream radiation collector side 252. Radiation crossing the collector CO may be reflected from a grating spectral filter 240 and focused on a virtual source point (IF) along an optical axis indicated by a dotted line'O'. The virtual source point IF is commonly referred to as an intermediate focus, and the source collector module is disposed such that the intermediate focus IF is located at or near the opening 221 in the enclosing structure 220. The virtual source point IF is an image of the radiation emitting plasma 210.

Subsequently, the radiation traverses the illumination system IL, so as to provide the desired uniformity of the radiation intensity in the patterning device MA, as well as the desired angular distribution of the radiation beam 21 in the patterning device MA. A faceted field mirror device 22 and a faceted pupil mirror device 24 may be disposed. Upon reflection of the radiation beam 21 in the patterning device MA held by the support structure MT, a patterned beam 26 is formed, and the patterned beam 26 is formed by the projection system PS. It is imaged through reflective elements 28 and 30 onto the substrate W held by the substrate table WT.

In general, more elements than shown may be present in the illumination optics unit IL and projection system PS. The grating spectral filter 240 may optionally be present depending on the type of lithographic apparatus. In addition, there may be more mirrors than shown in the figures, for example 1 to 6 additional reflective elements than shown in FIG. 18 may be present in the projection system PS.

The collector optics CO as illustrated in FIG. 18 is shown as a nested collector with grazing incident reflectors 253, 254 and 255, merely as an example of a collector (or collector mirror). The grazing incident reflectors 253, 254 and 255 are arranged axisymmetrically around the optical axis O, and this type of collector optics CO is preferably used in combination with a discharge generating plasma radiation source.

Alternatively, the source collector module SO may be part of an LPP radiation system as shown in FIG. 19. A laser (LAS) is arranged to deposit laser energy in a fuel such as xenon (Xe), tin (Sn) or lithium (Li), and has an electron temperature of several tens of eV. ). The energetic radiation generated during de-excitation and recombination of these ions is emitted from the plasma and collected by the near normal incidence collector optic (CO), and the enclosing structure The focus is on the opening 221 of the 220.

These embodiments can be further described using the following items:

1. As a method of determining candidate patterns from a set of patterns of a patterning process,

(I) a set of patterns in the patterning process, (ii) a search pattern having a first feature and a second feature, and (iii) a first search condition including a relative position between the first feature and the second feature of the search pattern. Obtaining step; And

Determining, via the processor, a first set of candidate patterns from a set of patterns that satisfy a first search condition associated with a first feature and a second feature of the search pattern.

2. The method of 1, wherein a relative position is defined between an element of a first feature and an element of a second feature of the search pattern.

3. The method of 2, wherein the element comprises an edge and/or vertex of each feature.

4. The method according to any one of items 1 to 3, wherein the first search condition further comprises a tolerance limit associated with the dimensions of the features and/or the relative position between the elements of the features.

5. The method of any one of items 1 to 4, wherein the first feature and the second feature are on the same layer.

6. The method of any one of items 1 to 4, wherein the first feature and the second feature are in different layers.

7. The method according to any one of items 1 to 6,

Obtaining a bounding box around the search pattern and a second search condition associated with the feature and bounding box of the search pattern; And

Determining, via the processor, a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the bounding box.

8. The method of 7 wherein the second search condition comprises a relative position between an edge of a bounding box and an edge of a feature of the search pattern.

9. The method of 8, wherein the relative position is a distance and/or angle between an edge of a bounding box and an edge of a feature of the search pattern.

10. The method of any of paragraphs 7-9, wherein the second search condition further comprises a tolerance limit associated with a relative position between the bounding box and the element of the feature of the search pattern.

11. The method of any of paragraphs 1-10, wherein the second search condition is associated with a feature of the search pattern closest to the bounding box.

12. The method of any of paragraphs 1 to 11, wherein determining the second set of candidate patterns further comprises comparing the at least one parameter of the feature of the search pattern with the corresponding at least one parameter of the feature of the set of patterns. How to include.

13. The method of 12, wherein the at least one parameter is:

The edge of the feature;

The size of the feature; And

A method comprising at least one of the topologies of the feature.

14. The method of any of paragraphs 1-13, wherein determining the second set of candidate patterns comprises:

Adjusting a bounding box around the search pattern based on a second search condition; And

The method further comprising determining a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the adjusted bounding box.

15. The method of 14, wherein adjusting the bounding box comprises increasing and/or decreasing the size of the bounding box for increasing and/or decreasing the size of the features of the pattern of the second search condition and the set of patterns. Way.

16. The method of 14, wherein the amount of increasing and/or decreasing the size of the bounding box is within a tolerance limit associated with the relative position between the bounding box and the elements of the features of the search pattern.

17. The method according to any one of items 1 to 16, wherein the set of patterns comprises a design pattern; And/or an image of patterns of the printed substrate; And/or simulated patterns of the substrate.

18. The method of 17, wherein the set of patterns is obtained from a scanning electron microscope image.

19. The method of 18, wherein the search pattern comprises a plurality of features, the plurality of features being in the same layer of the substrate and/or different layers of the substrate.

20. The method of any of paragraphs 1-19, wherein the second feature is adjacent to the first feature.

21. As a method of determining candidate patterns from a set of patterns,

(I) a first set of candidate patterns from a set of patterns based on a first search condition associated with features of the search pattern, (ii) a bounding box around the search pattern, and (iii) a feature and bounding box of the search pattern Obtaining a second search condition associated with; And

And determining a second set of candidate patterns from the first set of candidate patterns based on a second search condition.

22. The method of 21, wherein the second search condition is a distance and/or angle between an edge of a bounding box and an edge of a feature of the search pattern.

23. The method of 22, wherein the second search condition further comprises a tolerance limit associated with a distance and/or angle between the bounding box and an element of the feature of the search pattern.

24. The method of any one of 21-23, wherein determining the second set of candidate patterns comprises:

Comparing the one or more parameters of the feature of the search pattern with the corresponding one or more parameters of the feature of the set of patterns; And

Based on the comparison, the method further comprising selecting a subset of patterns from the first set of candidate patterns excluding patterns having a topology mismatch.

25. The method of 24, wherein the at least one parameter is:

The edge of the feature;

The size of the feature; And

A method comprising at least one of the topologies of the feature.

26. The method of any one of 21-25, wherein determining the second set of candidate patterns comprises:

Adjusting a bounding box around the search pattern based on a second search condition; And

The method further comprising determining a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the adjusted bounding box.

27. The method of 26, wherein adjusting the bounding box comprises increasing and/or decreasing the size of the bounding box as a function of the size of a feature of the set of patterns and a second search condition.

28. The method of 27, wherein the amount of increasing and/or decreasing the size of the bounding box is within a tolerance limit associated with the relative position between the bounding box and the elements of the features of the search pattern.

29. A method of determining candidate patterns from a set of patterns of a patterning process,

(I) a first set of candidate patterns from a set of patterns based on a first search condition associated with features of the search pattern, (ii) a bounding box around the search pattern, and (iii) a feature and bounding box of the search pattern Obtaining a second search condition associated with; And

Determining a second set of candidate patterns from the first set of candidate patterns based on a second search condition, wherein the second set of candidate patterns includes a candidate pattern having additional features not included in the search pattern. Way.

30. The method of 29, wherein the additional features are adjacent to and within the bounding box of the features of the search pattern.

31. The method of 29 or 30, wherein the additional feature is on the same layer and/or a different layer than the features of the search pattern.

32. The method of any one of 29-31, wherein the additional feature is not associated with constraints on the features of the bounding box or search pattern.

33. The method of any one of 29-32, wherein determining the second set of candidate patterns comprises:

Comparing the one or more parameters of the feature of the search pattern with the corresponding one or more parameters of the feature of the set of patterns; And

Based on the comparison, the method further comprising selecting patterns from the first set of candidate patterns without excluding patterns having a topology mismatch.

34. The method of 33, wherein the at least one parameter is:

The edge of the feature;

The size of the feature; And

A method comprising at least one of the topologies of the feature.

35. A method of determining candidate patterns from a set of patterns of a patterning process,

Applying, via an interface, a first condition between the first feature and the second feature of the search pattern;

Determining, through the processor, a first set of candidate patterns from the set of patterns based on the first constraint;

Drawing, via the interface, a bounding box around the search pattern;

Applying, via the interface, a second condition between the bounding box and the first feature or the second feature; And

Determining, through the processor, a second set of candidate patterns from the first set of candidate patterns based on a second condition, wherein the second set of candidate patterns has additional features not included in the search pattern. How to include.

36. The method of 35, wherein applying the first condition comprises:

Selecting an edge of a first feature and an edge of a second feature of the search pattern;

Allocating a distance between the selected edges; And/or

And assigning a tolerance limit to the distance between the selected edges.

37. As a method of creating a search pattern database,

Obtaining a set of patterns-the pattern of the set of patterns includes a plurality of features-;

Applying, via an interface, a set of search conditions to the set of patterns to generate a set of search patterns-the search pattern is associated with the search condition;

Evaluating, via the processor, whether there is a conflict between the one or more search conditions associated with the one or more features of the set of patterns; And

Storing, via the processor, a set of search patterns and associated search conditions for which there is no conflict.

38. The method of 37, wherein evaluating the collision comprises:

Identifying features of a set of patterns having the same search condition; And/or

Determining whether the search conditions exceed a preset threshold associated with a feature of the pattern in the set of patterns; And/or

A method comprising displaying the identified features to modify conditions to eliminate the conflict.

39. A computer program product comprising a non-transitory computer-readable medium having instructions recorded thereon,

A computer program product that, when the instructions are executed by a computer, implements the method of any one of items 1 to 38.

The concepts disclosed herein can simulate or mathematically model any common imaging system for imaging sub-wavelength features, and may be particularly useful with emerging imaging techniques capable of producing increasingly shorter wavelengths. Emerging technologies already in use include deep ultra violet (DUV) lithography, which can produce wavelengths of 193 nm using an ArF laser and even 157 nm using a fluorine laser. In addition, EUV lithography can generate wavelengths in the 20 to 5 nm range by hitting a material (solid or plasma) with high energy electrons to generate photons in this range, or by using a synchrotron.

While the concepts disclosed herein may be used for imaging on a substrate such as a silicon wafer, the disclosed concepts are used to image any type of lithographic imaging systems, e.g., on substrates other than silicon wafers. It should be understood that it can also be used as

While reference is made herein to specific uses of the embodiments in IC manufacturing, it should be understood that the embodiments herein may have a number of other possible applications. For example, it may be employed in the manufacture of integrated optical systems, guide and detection patterns for magnetic domain memories, liquid crystal displays (LCDs), thin-film magnetic heads, micromechanical systems (MEMS), and the like. Those of ordinary skill in the art, with regard to these alternative applications, any use of the terms "reticle", "wafer" or "die" herein is the more general term "patterning device", "substrate" or "target part", respectively. It will be understood that the term may be considered synonymous with or interchangeable. The substrate referred to herein may be processed before and after exposure, for example in a track (typically a tool that applies a layer of resist to the substrate and develops the exposed resist) or a metrology or inspection tool. If applicable, the description of this specification may apply to such substrate processing tools and other substrate processing tools. In addition, since the substrate may be processed more than once to produce a multilayer IC, for example, the term substrate as used herein may refer to a substrate including layers that have already been processed several times.

As used herein, the terms “radiation” and “beam” refer to particle beams such as ion beams or electron beams, as well as (e.g., about 365, about 248, about 193, about 157 or about 126 nm It encompasses all forms of electromagnetic radiation, including ultraviolet radiation (having a wavelength of 5 to 20 nm) and extreme ultraviolet (EUV) radiation (eg, having a wavelength in the range of 5 to 20 nm).

The terms “optimizing” and “optimizing” as used herein refer to a patterning apparatus such that results and/or processes have more desirable properties, such as higher projection accuracy of the design pattern on the substrate, larger process window, etc. It refers to or means adjusting (for example, a lithographic apparatus), a patterning process, and the like. Thus, the terms “optimizing” and “optimizing” as used herein refer to one or more that provide an improvement in at least one related metric, e.g., a local optimization, compared to an initial set of one or more values for one or more parameters. Refers to or refers to the process of identifying one or more values for a parameter. “Optimal” and other related terms are to be interpreted accordingly. In one embodiment, optimization steps may be applied iteratively to provide further improvement in one or more metrics.

Embodiments of the present invention can be implemented in any convenient form. For example, one embodiment is by one or more suitable computer programs that can be delivered on a suitable delivery medium, which can be a tangible delivery medium (e.g., disk) or an intangible delivery medium (e.g., a communication signal). Can be implemented. Embodiments of the present invention may be implemented using any suitable device that may take the form of a programmable computer that executes a computer program that is specifically arranged to implement the methods described herein. Accordingly, embodiments of the present invention may be implemented in hardware, firmware, software, or any combination thereof. Further, embodiments of the present invention may be implemented as instructions stored on a machine-readable medium, which may be read and executed by one or more processors. Machine-readable media may include any mechanism for storing or transmitting information in a form readable by a machine (eg, a computing device). For example, machine-readable media may include read only memory (ROM); Random access memory (RAM); Magnetic disk storage media; Optical storage media; Flash memory device; Electrical, optical, acoustic, or other forms of propagated signals (eg, carrier waves, infrared signals, digital signals, etc.), and others. In addition, firmware, software, routines, and instructions may be described as performing a predetermined operation in this specification. However, it is to be understood that these descriptions are for convenience only, and that such operation takes place in fact from a computing device, processor, controller, or other devices executing firmware, software, routines, instructions, and the like.

In block diagrams, the illustrated components are shown as individual functional blocks, but embodiments are not limited to systems in which the functionality described herein is configured as illustrated. The functionality provided by each of the components may be provided by software or hardware modules configured differently from those currently shown, for example such software or hardware (e.g., within a data center or geographically ) Can be mixed, combined, replicated, separated, distributed, or otherwise configured differently. The functionality described herein may be provided by one or more processors of one or more computers executing code stored on a tangible non-transitory machine-readable medium. In some cases, third-party content delivery networks may host some or all of the information delivered over the network, in which case, to the extent that the information (e.g., content) is supplied or otherwise provided, the information is the content delivery. It can be provided by sending instructions to retrieve that information from the network.

Unless specifically stated otherwise, as will be apparent from the discussion, descriptions using terms such as "processing", "calculation", "calculation", "determining" and the like throughout this specification are It is understood that it refers to the operation or process of a particular apparatus, such as a processing/computation device.

It should be understood that this application describes several inventions. Rather than separating these inventions into a number of individual patent applications, these inventions have been grouped into a single document, since their subject matter is suitable for savings in the filing process. However, the separate advantages and aspects of these inventions should not be combined. In some cases, although the embodiments solve all of the drawbacks specified herein, the present inventions are useful independently, and some embodiments solve only a subset of these problems, or others not mentioned that will be apparent to those skilled in the art reviewing the present disclosure. It should be understood that it provides advantages. Due to cost constraints, some inventions disclosed herein may not be claimed at this time, and may be claimed in later applications, such as by amendment to this claim or as a continuing application. Similarly, due to space constraints, the Abstract or Summary portions of this document should not be considered as an exhaustive list of all such inventions or as including all embodiments of such inventions.

The description and drawings are not intended to limit the present invention to the specific form disclosed, but, on the contrary, that the present invention is intended to cover all modifications, equivalents and alternatives within the spirit and scope of the present invention as defined by the appended claims. You must understand.

Variations and alternative embodiments of the various embodiments of the present invention will be apparent to those skilled in the art in view of this description. Accordingly, these descriptions and drawings are to be construed as illustrative only, and are intended to teach those skilled in the art a general manner of carrying out the present invention. It is to be understood that the aspects of the invention shown and described herein have been taken as examples of embodiments. Elements and materials may be substituted for those shown and described herein, parts and processes may be reversed or omitted, certain features may be used independently, and embodiments or features of embodiments They can be combined, which will be apparent to those skilled in the art after all have the advantage of this description. Elements described herein may be changed without departing from the spirit and scope of the present invention as set forth in the following claims. The headings used herein are for organizational purposes only and are not used to limit the scope of the description.

As used throughout this application, the word “may” is used in the sense of permissive (ie, means to have a possibility) rather than in an obligatory sense (ie, to mean a must). Words such as “comprises” and “comprising” are meant to include, but are not limited to. As used throughout this application, the singular forms “a”, “an” and “the” include plural objects unless the content expressly dictates otherwise. Thus, for example, reference to “a” element includes a combination of two or more elements despite the use of other terms and phrases for one or more elements, such as “one or more”. The term “or” is non-exclusive, ie includes both “and” and “or” unless otherwise specified. For example, terms describing conditional relationships such as "In response to X, Y", "When X, Y", "If X, Y", "For X, Y", etc. Or, the prerequisite is a sufficient causal condition, or the predecessor encompasses causal relationships where the contributing causal condition of the result, for example, "state X occurs when the condition Y is obtained", "X occurs only in Y" And "X occurs in Y and Z". These conditional relationships are not limited to results immediately after obtaining a prerequisite because some results may be delayed, and in a conditional statement, the prerequisite is linked to the results, e.g. the predicate is related to the likelihood of occurrence of the result. have. References that a plurality of attributes or functions are mapped to a plurality of objects (e.g., one or more processors performing Step A, Step B, Step C and Step D) refer to all such objects unless otherwise indicated. All of these attributes or functions that are mapped, and both of the attributes or subsets of functions that are mapped to the attributes or subsets of functions (e.g., all processors performing steps A through D, respectively, And a case where processor 1 performs step A, processor 2 performs part of steps B and C, and processor 3 performs part of step C and step D). Further, unless otherwise indicated, the reference that one value or action is "based on" another condition or value means instances where the condition or value is the only factor and the condition or value is one of a plurality of factors. It encompasses both instances of phosphorus. Unless otherwise indicated, references that an instance of "each" of some set has some properties should not be read as except where some other identical or similar members of a larger set do not have that property, i.e. Each does not necessarily mean each and every. References to selection from a range include the end points of the range.

In the preceding description, any processes, descriptions, or blocks in the flowchart represent portions of code that include one or more executable instructions for implementing specific logical functions or steps in modules, segments or processes. It should be understood that, and as those skilled in the art will appreciate, alternative implementations in which the functions may be executed out of the order shown or discussed, including those performed substantially simultaneously or in reverse order depending on the relevant function, are exemplary implementations of the present invention. Included within the scope of examples.

To the extent that certain U.S. patents, U.S. patent applications, or other materials (e.g., articles) are cited, the text of such U.S. patents, U.S. patent applications, and other materials is a conflict between these materials and the description and drawings set forth herein It is cited only to the extent that it does not. In case of such conflict, any such conflicting text in such cited US patents, US patent applications, and other materials is not specifically incorporated herein by reference.

While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the invention. Indeed, the novel methods, apparatuses and systems described herein can be implemented in a variety of different forms; In addition, various omissions, substitutions, and changes in the form of the methods, devices and systems described herein may be made without departing from the spirit of the present invention. The appended claims and their equivalents are intended to cover such forms or variations that fall within the spirit and scope of the present invention.

Claims (15)

A method of determining candidate patterns from a set of patterns of a patterning process, comprising:
(I) a set of patterns in the patterning process, (ii) a search pattern having a first feature and a second feature, and (iii) a relative position between the first feature and the second feature of the search pattern Obtaining a first search condition including; And
Determining, through a processor, a first set of candidate patterns from the set of patterns that satisfy the first search condition associated with the first feature and the second feature of the search pattern.
How to include. The method of claim 1,
The relative position is defined between an element of a first feature and an element of a second feature of the search pattern. The method of claim 2,
The method of the element comprises an edge and/or vertex of each feature. The method of claim 1,
The first search condition further comprises a tolerance limit associated with a dimension of the features and/or a relative position between elements of the features. The method of claim 1,
The first feature and the second feature are on the same layer. The method of claim 1,
The method wherein the first feature and the second feature are in different layers. The method of claim 1,
Obtaining a bounding box around the search pattern and a feature of the search pattern and a second search condition associated with the bounding box; And
Determining, via the processor, a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the bounding box. The method of claim 7,
The second search condition includes a relative position between an edge of the bounding box and an edge of a feature of the search pattern, and/or
The relative position is a distance and/or angle between an edge of the bounding box and an edge of a feature of the search pattern. The method of claim 7,
The second search condition further comprises a tolerance limit associated with a relative position between the bounding box and an element of the feature of the search pattern. The method of claim 1,
The second search condition is associated with a feature of the search pattern closest to the bounding box. The method of claim 1,
The method of determining the second set of candidate patterns further comprises comparing one or more parameters of a feature of the search pattern with a corresponding one or more parameters of a feature of the set of patterns. The method of claim 11,
The one or more parameters are:
The edge of the feature;
The size of the feature; And
A method comprising at least one of the topologies of the feature. The method of claim 1,
The step of determining the second set of candidate patterns is:
Adjusting a bounding box around the search pattern based on a second search condition; And
The method further comprising determining a second set of candidate patterns from the first set of candidate patterns that satisfy a second search condition associated with the adjusted bounding box. The method of claim 13,
The step of adjusting the bounding box comprises increasing and/or decreasing the size of the bounding box in response to the second search condition and increasing and/or decreasing the size of a feature of the pattern of the set of patterns. The method of claim 1,
The set of patterns may include a design pattern; And/or an image of patterns of the printed substrate; And/or simulated patterns of the substrate.

Images